API Rate Limits Compared: Every Major LLM Provider (November 2026)

Twelfth edition. The eleventh (October 17, 2026) covered 17 providers. This update reflects the three-and-a-half-week window since October 17. Meta’s current flagship is now Muse Wonder / Muse Wonder Full (October 2026), built for personal and professional agentic tasks. GPT-4.1 Nano shut down October 23, 2026 — that deadline has passed. GPT-4.1 and GPT-4.1 Mini remain callable until January 14, 2027. All other headline model positions are unchanged from the eleventh edition: OpenAI GPT-6 Astra, Anthropic Fable 5.1 / Opus 5.5 / Sonnet 5.5 / Haiku 5.5, Google Gemini 4 Argon, xAI Grok 4.7, DeepSeek V4.1-Flash, Mistral Large 4 (still public preview). Rate limit tables for most models introduced since August 2026 remain unpublished — predecessor figures are carried forward as provisional floors throughout.

What changed since October 17
Free Tier — RPM & RPD
Free Tier — TPM & TPD
Entry Paid Tier — RPM & RPD
Entry Paid Tier — TPM
Scaled Tier — RPM & TPM
Cerebras & SambaNova
Audio Models — ASH & ASD
Cloud Aggregators — Azure AI & AWS Bedrock
More Providers — Perplexity, Alibaba, Moonshot
Provider Notes
Tips for managing rate limits
Further Reading

Last updated: November 10, 2026.

What changed since October 17

GPT-4.1 Nano is gone. The October 23, 2026 shutdown date has passed. Any pipeline still referencing gpt-4.1-nano is receiving errors. GPT-6 Luna ($0.10/$0.50 per M) is the named replacement. GPT-5.4 Mini ($0.75/$4.50 per M) is an intermediate option if Luna is too stripped-down for a given workload.

GPT-4.1 and GPT-4.1 Mini remain callable until January 14, 2027. Deprecated October 14, 2026 but not yet shut down. Pipelines on these models have approximately two months remaining. GPT-6 Luna is the named replacement for both.

Meta’s current flagship is Muse Wonder / Muse Wonder Full. Released October 2026. Built for personal and professional agentic tasks — navigating an insurance claim, making sense of a lease, building a working app. Available to developers via the Meta Model API and Muse Code; Muse Wonder Full is available to Muse Code subscribers. No per-token pricing has been confirmed for either model — no price is quoted in this post. Muse Spark 1.3 (long-horizon coding and agentic work) and Muse Spark 1.1 (July 2026) are previous-generation Meta proprietary models. The Llama 4 open-weight family (Scout, Maverick) is unchanged.

Gemini 4 Argon introductory pricing window is narrowing. Introductory rates ($2/$10 per M) expire November 30, 2026 — twenty days from this edition’s publish date. Standard rates double to $4/$20 on January 1, 2027. Cost models projecting past November 30 must use the standard rate. The larger-prompt tier at $4/$20 also exists at introductory pricing, but its exact token threshold remains unconfirmed — do not quote a specific cutoff.

Gemini 3.8 / 3.7 / 3.6 Flash introductory pricing expires December 31, 2026. Standard rate of $1.50/$7.50 per M applies from January 1, 2027. Any cost model using $0.75/$3.75 for dates past December 31 is wrong.

GPT-5.4 Nano shutdown approaching. Deprecated October 1, 2026; shuts down April 1, 2027. Five months remaining. GPT-6 Luna is the named replacement.

No new rate limit tables published. OpenAI, Anthropic, Google, xAI, DeepSeek, Alibaba, and Moonshot have not published rate limit figures for their models introduced since August 2026. All provisional floors from the eleventh edition are carried forward unchanged.

Still pending formal documentation:

OpenAI: GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna rate limit tier tables not yet published. GPT-5.5 figures carried forward as provisional floors.
Anthropic: Claude Opus 5.5, Sonnet 5.5, Haiku 5.5, and Fable 5.1 rate limit figures not yet published. Predecessor figures carried forward as provisional floors.
Google: Gemini 4 Argon rate limit figures not yet published. Gemini 3.8 Flash, 3.7 Flash, 3.6 Flash, 3.5 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber rate limit figures also unpublished. Gemini 3.5 Pro remains in limited preview.
xAI: Grok 4.7 and Grok 4.6 numerical rate limit figures console-only, not in public documentation.
DeepSeek: Fully dynamic concurrency limits; no published RPM/TPM for any model.
Alibaba: Qwen3.8-Max rate limit figures not yet published. Qwen3.7-Max limits carried forward as a provisional floor.
Moonshot: Kimi K3 rate limit figures not yet confirmed in public documentation. K2.5 figures carried forward.
Mistral: Numerical limits require login at admin.mistral.ai. Large 4 pricing unconfirmed.
Meta: Muse Wonder and Muse Wonder Full rate limit figures not yet published. No per-token pricing confirmed.

Deprecation calendar — updated:

GPT-4.1 Nano: shut down October 23, 2026 — passed. Migrate to GPT-6 Luna now.
GPT-4.1 and GPT-4.1 Mini: deprecated October 14, 2026; shut down January 14, 2027. ~two months remaining.
GPT-5.4 Nano: deprecated October 1, 2026; shuts down April 1, 2027.
Gemini 4 Argon introductory pricing: expires November 30, 2026 — twenty days away. Rates double January 1, 2027.
Gemini 3.8 Flash / 3.7 Flash / 3.6 Flash introductory pricing: expires December 31, 2026. Standard $1.50/$7.50 from January 1, 2027.
OpenAI Assistants API: deprecated August 2026 — passed. Migrate to the Responses API.
DeepSeek V3.2 aliases: deprecated July 24, 2026 — passed. Those endpoints are gone.

What are rate limits?

Rate limits cap how much you can use an API within a given time window. Providers enforce them to manage capacity and ensure fair access. Exceeding a limit returns a 429 Too Many Requests error.

Most providers use the token bucket algorithm: capacity refills continuously up to your maximum, rather than resetting at fixed intervals. A 60 RPM limit means roughly 1 request per second with steady refill, not 60 requests then a hard stop.

The metrics

RPM (Requests per minute): API calls per minute, regardless of size. A 10-token request and a 100K-token request both count as one.
RPD (Requests per day): Daily cap on total API calls. Some providers use this instead of (or alongside) RPM, especially on free tiers.
TPM (Tokens per minute): Total tokens (input + output) processed per minute. Usually the binding constraint in production.
TPD (Tokens per day): Daily token cap. More common on free tiers.
ITPM/OTPM (Input/Output tokens per minute): Anthropic separates input and output token limits, giving finer control. Cached input tokens don’t count toward ITPM on current Claude 4.x and 5.x models.
ASH/ASD (Audio seconds per hour/day): For speech models like Whisper.

RPM limits set your concurrency ceiling. TPM limits set your throughput. For batch workloads, RPD and TPD matter more. For real-time apps, RPM and TPM hit first.

Free Tier — Requests per Minute (RPM) & Requests per Day (RPD)

Provider / Model	RPM	RPD
Google — Gemini 3.1 Flash-Lite	15	1,000
Groq — Llama 4 Scout	30	1,000
Cerebras — Llama 4 Scout	30	—
SambaNova — open models	10–30	—
Fireworks AI — OS models	10	—
Cohere — Command R+*	20	~33†

*Cohere’s free tier figures reference Command R+. Command A+ free tier limits not yet published. †Cohere trial keys get 1,000 calls/month across all endpoints, roughly ~33/day.

Note: Gemini 4 Argon is paid tier only — no free tier exists for it. Gemini 3.8 Flash, 3.7 Flash, 3.6 Flash, 3.5 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber free tier rate limit figures are not yet published in public documentation. Gemini 3.1 Flash-Lite figures shown above are the last confirmed published numbers. OpenAI, Anthropic, xAI, DeepSeek, and Mistral have no free API tier for current flagship models. OpenAI’s free tier does not support any GPT-5.x or GPT-6.x model via the API. Anthropic’s lowest entry is $5 (Tier 1). xAI and Mistral gate numerical limits behind their respective consoles.

Migration note: GPT-4.1 Nano shut down October 23, 2026 — that deadline has passed. Any pipeline on gpt-4.1-nano is dead. DeepSeek V3.2 aliases deprecated July 24, 2026 — also passed.

Free Tier — Tokens per Minute (TPM) & Tokens per Day (TPD)

Provider / Model	TPM	TPD
Google — Gemini 3.1 Flash-Lite	250,000	—
Groq — Llama 4 Scout	30,000	500,000
Groq — other open models	6,000–30,000	500,000
Cerebras — Llama 4 Scout	60,000	1,000,000
SambaNova (free tier)	—	—

Standout: Google leads with 250K TPM on the free tier for Gemini 3.1 Flash-Lite, but the 10–15 RPM ceiling means it’s best suited to fewer, larger requests. Gemini 4 Argon, 3.8 Flash, 3.7 Flash, 3.6 Flash, 3.5 Flash, and 3.5 Flash-Lite free tier TPM figures are not yet published. Cerebras offers 60K TPM with 1M TPD and approximately 2,100 tokens/second inference speed on Llama 4 Scout — the fastest free option by throughput. SambaNova publishes RPM but not TPM/TPD specifics.

Entry Paid Tier — Requests per Minute (RPM) & Requests per Day (RPD)

The tier most developers start with. OpenAI Tier 1 ($5), Anthropic Tier 1 ($5), Google Tier 1 (pay-as-you-go), and others at their lowest paid level.

Provider / Model	RPM	RPD
OpenAI — GPT-6 Astra*	500*	—
OpenAI — GPT-6 Luna*	500*	—
Anthropic — Fable 5.1†	50†	—
Anthropic — Opus 5.5†	50†	—
Anthropic — Sonnet 5.5†	50†	—
Anthropic — Haiku 5.5†	50†	—
Google — Gemini 3.1 Pro	150	1,000
Google — Gemini 3.1 Flash-Lite	300	1,500
xAI — Grok 4.7	Console‡	—
DeepSeek — V4.1-Flash	Dynamic§	—
Fireworks AI — OS models	≤6,000	—
Cohere — Command A+**	500**	—

*GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna rate limit tier tables not yet published. 500 RPM carried forward from GPT-5.5 as a provisional floor. †Fable 5.1, Opus 5.5, Sonnet 5.5, and Haiku 5.5 rate limit tier tables not yet published. 50 RPM carried forward from their respective predecessors as a provisional floor. ‡xAI publishes tier thresholds ($0/$50/$250/$1K/$5K) but numerical RPM/TPM are only visible in the xAI Console after login. §DeepSeek uses fully dynamic concurrency limits based on server load. No fixed RPM/TPM published. **Command A+ entry paid tier limits not yet published. 500 RPM is the Command R+ figure, carried forward as a reference.

Gemini 4 Argon and 3.8 Flash note: Neither model has published rate limit figures in public documentation. Gemini 3.7 Flash, 3.6 Flash, and 3.5 Flash also have no published rate limit figures. Gemini 3.1 Pro and 3.1 Flash-Lite remain the previous generation with the last confirmed published figures. Check AI Studio (aistudio.google.com/rate-limit) for your project’s actual limits.

Mistral note: Mistral moved to console-only limits. Actual numbers require login at admin.mistral.ai/plateforme/limits. Mistral is excluded from RPM columns where no public figure exists.

Standout: Fireworks can spike to 6,000 RPM but it’s a dynamic ceiling, not guaranteed (soft limit starts at approximately 1 RPS and doubles hourly). Anthropic’s 50 RPM at Tier 1 is the lowest here, but jumps 20x to 1,000 RPM at Tier 2 ($40). The ~30%-more-tokens tokenizer now applies to all Claude 4.7-generation models and later — TPM headroom shrinks faster for any model in that range than it did on Sonnet 4.6 or earlier at the same RPM.

Entry Paid Tier — Tokens per Minute (TPM)

Provider / Model	TPM
OpenAI — GPT-6 Astra*	500K*
OpenAI — GPT-6 Luna*	500K*
Anthropic — Fable 5.1†	30K in / 8K out†
Anthropic — Opus 5.5†	30K in / 8K out†
Anthropic — Sonnet 5.5†	30K in / 8K out†
Anthropic — Haiku 5.5†	50K in / 10K out†
Google — Gemini 3.1 Pro	1M
Google — Gemini 3.1 Flash-Lite	2M
DeepSeek — V4.1-Flash	Dynamic

*GPT-6 Astra and GPT-6 Luna TPM figures not yet published. 500K carried forward from GPT-5.5 as a provisional floor. †Fable 5.1, Opus 5.5, Sonnet 5.5, and Haiku 5.5 TPM figures not yet published. Predecessor figures carried forward as provisional floors.

Standout: Google’s 3.1 Flash-Lite leads confirmed figures at 2M TPM. Anthropic’s current models all carry the ~30%-more-tokens tokenizer (Claude 4.7 generation and later), meaning identical prompts now consume more tokens against ITPM limits than they did on Sonnet 4.6 or earlier. Cached input tokens don’t count toward ITPM on Claude 4.x and 5.x models — with an 80% cache hit rate, effective throughput remains substantially higher than the raw ITPM figure.

Scaled Tier — RPM & TPM at Higher Spend

For teams past entry-level. OpenAI Tier 3 ($100+), Anthropic Tier 3 ($200+), Google Tier 2 ($250+).

Provider (Tier) / Model	RPM	TPM
OpenAI (Tier 3) — GPT-6 Astra*	5,000*	2M*
OpenAI (Tier 3) — GPT-6 Luna*	5,000*	4M*
Anthropic (Tier 3) — Fable 5.1†	2,000†	800K in / 160K out†
Anthropic (Tier 3) — Opus 5.5†	2,000†	800K in / 160K out†
Anthropic (Tier 3) — Sonnet 5.5†	2,000†	800K in / 160K out†
Anthropic (Tier 3) — Haiku 5.5†	2,000†	1M in / 200K out†
Google (Tier 2) — Gemini 3.1 Pro	1,000	2M
Google (Tier 2) — Gemini 3.1 Flash-Lite	2,000	4M

*GPT-6 Astra and GPT-6 Luna Tier 3 figures not yet published. GPT-5.5 figures carried forward as a provisional floor. †Fable 5.1, Opus 5.5, Sonnet 5.5, and Haiku 5.5 Tier 3 figures not yet published. Predecessor figures carried forward as provisional floors.

At the highest standard tiers (OpenAI Tier 5 at $1,000+, Anthropic Tier 4 at $400+):

Provider (Tier) / Model	RPM	TPM
OpenAI (Tier 5) — GPT-6 Astra*	15,000*	40M*
OpenAI (Tier 5) — GPT-6 Luna*	30,000*	180M*
Anthropic (Tier 4) — Fable 5.1†	4,000†	2M in / 400K out†
Anthropic (Tier 4) — Opus 5.5†	4,000†	2M in / 400K out†
Anthropic (Tier 4) — Sonnet 5.5†	4,000†	2M in / 400K out†
Anthropic (Tier 4) — Haiku 5.5†	4,000†	4M in / 800K out†

*GPT-6 Astra and GPT-6 Luna Tier 5 figures not yet published. GPT-5.5 figures carried forward as a provisional floor. GPT-6 Luna’s provisionally carried figure at Tier 5 inherits GPT-4.1 Nano’s 180M TPM — treat with extra caution until official figures publish. †Fable 5.1, Opus 5.5, Sonnet 5.5, and Haiku 5.5 Tier 4 figures not yet published. Predecessor figures carried forward as provisional floors. Confirm current limits in the Anthropic console.

Standout: OpenAI’s Tier 5 numbers remain the highest of any provider with published or provisionally carried figures. GPT-6 Luna at a provisionally carried 180M TPM and 30K RPM is built for high-volume classification and routing — but the GPT-4.1 Nano figures those numbers are inherited from are from a now-shutdown model, so treat them as a rough floor only. Anthropic’s Tier 4 caps at 4K RPM, but cached tokens don’t count toward ITPM — effective throughput can be substantially higher with good cache hit rates.

Model pool notes:

Fable 5.1 pool assignment is not yet formally documented. Check your Anthropic dashboard.
Opus 5.5 pool assignment is not yet formally documented. Opus 4.8, 4.7, and 4.6 shared one rate limit bucket — check your dashboard for how the 5.x Opus line is bucketed.
Sonnet 5.5 and Sonnet 5 likely share a pool — not formally confirmed; check your dashboard.
Sending traffic to multiple model versions within the same pool draws from one shared bucket, not separate ones.

Gemini 4 Argon and 3.8 Flash scaled tier note: Neither model has published rate limit figures. Gemini 3.7 Flash, 3.6 Flash, and 3.5 Flash are also without published figures. The 3.1 Flash-Lite and 3.1 Pro figures shown above remain the last confirmed published numbers for Google’s API.

Cerebras & SambaNova

Both specialize in custom silicon for inference speed.

Cerebras

Hardware: Wafer-Scale Engine (WSE-3). Fastest published inference: approximately 2,100 tokens/second on Llama 4 Scout.

Tier	RPM	TPM	TPD
Free	30	60,000	1,000,000
Paid	Higher (contact sales)	Higher	Higher

Hosts Llama 4 Scout and other open models. The speed advantage is real: tasks that take 30 seconds on GPU-based providers finish in under 5 seconds on the WSE-3. Paid tier limits are not publicly documented.

SambaNova

Hardware: Custom RDU (Reconfigurable Dataflow Unit). Best time-to-first-token (TTFT): approximately 0.2 seconds.

Tier	RPM	Notes
Free	10–30 (varies by model)	Hosts up to Llama 4 Maverick for free

SambaNova offers Llama 4 Maverick (1M context) on the free tier — most other free-tier providers cap out at smaller models. TPM and TPD limits are not publicly documented.

Audio Models — ASH & ASD

Groq and Fireworks both publish audio-specific limits.

Provider / Model	RPM	RPD	ASH	ASD	Audio min/min
Groq (Free) — Whisper Large v3	20	2,000	7,200	28,800	—
Groq (Free) — Whisper Large v3 Turbo	20	2,000	7,200	28,800	—
Fireworks AI — Whisper v3-large	—	—	—	—	200
Fireworks AI — Whisper v3-turbo	—	—	—	—	400

Groq: 7,200 ASH = 2 hours of audio per hour of wall time. 28,800 ASD = 8 hours per day. Adequate for a podcast transcription pipeline on the free tier.

Fireworks: 200 min/min for Whisper v3-large, 400 min/min for v3-turbo. Concurrent streaming capped at 10 connections.

OpenAI’s GPT Transcribe and GPT Live Transcribe are available via API. Independent benchmarks show both lag ElevenLabs, Google, and Mistral on error rates. OpenAI does not yet publish audio-specific ASH/ASD figures for these endpoints in its public rate limit documentation.

Cloud Aggregators — Azure AI & AWS Bedrock

Both use configurable per-deployment limits, not fixed tiers. The shared ratio is 6 RPM per 1,000 TPM.

Azure AI (Microsoft)

Deployment Type	How Limits Work
Pay-as-you-go (Standard)	TPM quota per model per region, auto-scales with usage
Provisioned (PTU)	Reserved throughput units, no per-request limits
Global/Data Zone	Higher default quotas, multi-region routing

GPT-5.6 Sol remains the default in Microsoft 365 Copilot. Azure AI hosts GPT-6 Astra, GPT-6.1 Sol, GPT-5.6 Sol, GPT-5.5, GPT-5.4, Claude Fable 5.1/Opus 5.5/Sonnet 5.5, and Gemini 3.1 Pro across regions. Gemini 4 Argon, 3.8 Flash, 3.7 Flash, and 3.6 Flash availability on Azure is not yet confirmed — verify model and region availability before planning deployments. PTU deployments remove per-request limits. Azure AI Quotas & Limits

AWS Bedrock

Hosts Claude (Fable 5.1, Opus 5.5, Sonnet 5.5, Haiku 5.5, and legacy models), Llama 4, Mistral, and Nova models with per-model, per-region quotas. Amazon is scaling back most Nova AI models (Premier, Omni, Reel, Canvas into “keep the lights on” mode) while a new Frontier research team works on a foundation model expected at re:Invent. Default quotas vary by model and can be increased via the AWS Service Quotas console. Provisioned Throughput deployments remove rate limits entirely. AWS Bedrock Quotas

More Providers — Perplexity, Alibaba (Qwen), Moonshot (Kimi)

Provider / Model	RPM (T0)	RPM (T1)	RPM (T3+)	TPM	TPD (T0)
Perplexity — Sonar Pro	50	150	1,000	—	—
Perplexity — Sonar	50	150	1,000	—	—
Perplexity — Deep Research	5	10	40	—	—
Alibaba (Qwen) — Qwen3.8-Max*	—	600*	600*	1M*	—
Alibaba (Qwen) — Qwen3.7-Max†	—	600†	600†	1M†	—
Alibaba (Qwen) — Qwen3.5 Plus	—	15,000	30,000	5M	—
Alibaba (Qwen) — Qwen3.5 Flash	—	15,000	30,000	10M	—
Moonshot — Kimi K3‡	3‡	200‡	5,000‡	—	1.5M‡
Moonshot — Kimi K2.5	3	200	5,000	—	1.5M

*Qwen3.8-Max rate limit figures not yet published. Qwen3.7-Max figures carried forward as a provisional floor. Qwen3.8-Max per-token pricing is not published — do not use any per-token figure for it. Qwen3.8-Max weights are now openly released as Qwen3.8-2.4T-A95B on Hugging Face and ModelScope. †Qwen3.7-Max rate limit figures not yet formally published. Qwen3 Max limits carried forward as a provisional floor. ‡Kimi K3 rate limit figures not yet confirmed in Moonshot’s public documentation. K2.5 figures carried forward as a provisional floor.

Perplexity tiers: T0 = new account, T1 = $50+, T3 = $500+. Alibaba limits shown for international (Singapore) deployment; Beijing deployment is more generous (Qwen3.5 Flash at 30K RPM — Qwen3.8-Max and 3.7-Max Beijing limits not yet confirmed). Moonshot T1 = $10+ cumulative recharge; T0 has 1.5M TPD cap, T1+ is unlimited.

Standout: Alibaba’s Qwen3.5 Flash at 30K RPM / 10M TPM (Beijing) remains the highest confirmed throughput of any provider in this post. Moonshot’s T5 tier (10K RPM, 1,000 concurrent connections, $3,000+ recharge) is competitive at the high end. Kimi K3’s 2.8T parameters and Opus-class performance at Sonnet-level pricing make it a meaningful option for high-volume workloads — confirmed rate limit figures are still absent from Moonshot’s public documentation.

Provider Notes

OpenAI: GPT-6 Astra (September 2026; gpt-6-astra; 1,050,000 context, 128K max output; $10/$50 per M — prompts over 272K input tokens bill at 2x input/cache and 1.5x output for the whole request; Fast mode up to 2x speed at 2x price) is the current flagship. GPT-6.1 Sol (September 29; gpt-6.1-sol; $2/$10 per M, cached $0.10; nearly matches Astra on agentic coding, computer use, and professional work at approximately one-fifth of Astra’s token prices). GPT-6 Luna (September 22; gpt-6-luna; $0.10/$0.50 per M, cached $0.01; OpenAI’s cheapest current model and the named replacement for the GPT-4.1 family and GPT-5.4 Nano). Rate limit tier tables for GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna not yet published — GPT-5.5 figures carried forward as provisional floors. GPT-5.6 Sol ($4/$20 per M), GPT-5.6 Terra ($2/$12), GPT-5.6 Luna ($0.20/$1.20). GPT-5.5 ($5/$30 per M; variants: GPT-5.5 Thinking, GPT-5.5 Pro). GPT-5.5 Instant remains available. GPT-5.4 ($2.50/$15 per M; variants: GPT-5.4 Thinking, GPT-5.4 Pro, GPT-5.4-Cyber for vetted security teams). GPT-5.4 Mini ($0.75/$4.50 per M) still available. GPT-5.3 Codex consolidated into ChatGPT. GPT-5.2 being phased out. DEPRECATED/SHUT DOWN: GPT-4.1 Nano shut down October 23, 2026 — gpt-4.1-nano calls now fail. GPT-4.1 and GPT-4.1 Mini deprecated October 14, 2026; shut down January 14, 2027. GPT-5.4 Nano deprecated October 1, 2026; shuts down April 1, 2027. GPT-6 Luna is the named replacement for all of these. GPT-4 and GPT-4o retired February 2026. GPT Transcribe and GPT Live Transcribe available via API; audio-specific rate limit figures not yet published. Assistants API deprecated August 2026 — migrate to the Responses API. Batch API offers 50% discount with higher queue limits. Docs
Anthropic: Current lineup as of November 2026 is Claude Fable 5.1 / Opus 5.5 / Sonnet 5.5 / Haiku 5.5 — all 1M context, 128K max output, June 2026 reliable knowledge cutoff. Anthropic’s guidance is to start with Opus 5.5 for most workloads and reach for Fable 5.1 for demanding reasoning and long-horizon agentic work. Claude Fable 5.1 (September 1; claude-fable-5-1; $10/$50 per M, cache reads $0.25): top-capability tier; can identify software vulnerabilities in source code; biology safeguards intervene on benign requests 85% less often than Fable 5. Claude Opus 5.5 (September 22; claude-opus-5-5; $4/$20 per M, cache reads $0.20): recommended starting point; always-on adaptive thinking, default effort medium. Claude Sonnet 5.5 (September 28; claude-sonnet-5-5; $2/$10 per M, cache reads $0.10): current balanced tier; adaptive thinking, default effort high. Claude Haiku 5.5 (October 7; claude-haiku-5-5): current fast/budget tier; tiered pricing: $0.10/$0.50 per M for prompts up to 100,000 tokens, $0.50/$2.50 above that. Rate limit figures for all four not yet published — predecessor figures carried forward as provisional floors. Claude Mythos 5.1 (same underlying model as Fable 5.1; invitation-only via Project Glasswing — not generally available). Claude Fable 5 (June 9, 2026) and legacy models remain available. Sonnet 5 and Sonnet 5.5 pricing is $2/$10 per M permanently — not introductory. Sonnet 4.6 is $3/$15. Extended thinking (thinking.type "enabled" plus budget_tokens) is deprecated on Opus 4.6 and Sonnet 4.6 and is NOT accepted on later models — use the effort parameter for adaptive thinking on current models. The ~30%-more-tokens tokenizer arrived with the Claude 4.7 generation: Claude 4.7 and later use it; Sonnet 4.6 and earlier use the previous one. Cached input tokens don’t count toward ITPM on current 4.x and 5.x models. No free tier; lowest entry is $5. Claude 3 Haiku retired April 2026. Docs
Google: Static rate limit tables removed from public docs in Q1 2026. Actual limits only visible in AI Studio dashboard (aistudio.google.com/rate-limit). Gemini 4 Argon (October 13, 2026; gemini-4-argon) is the current flagship — 1M unified context, up to 1M output tokens with long decode (65,536 default), ranked #1 on the Vals Index; introductory $2/$10 per M through November 30, 2026, doubling January 1, 2027; larger-prompt tier at $4/$20 but exact threshold unconfirmed. Paid tier only. Rate limit figures not yet published. Gemini 3.8 Flash (September 2, 2026; gemini-3.8-flash): most intelligent Flash model, GA; 1M context, 64K max output, tunable thinking levels; introductory $0.75/$3.75 per M through December 31, 2026, rising to $1.50/$7.50 January 1, 2027; rate limit figures not yet published. Gemini 3.8 Flash Cyber (cybersecurity domain) launched alongside it. Gemini 3.7 Flash (previous flagship, still GA, still the default for Antigravity; same introductory pricing; rate limit figures not yet published). Gemini 3.6 Flash (still GA; same introductory pricing; rate limit figures not yet published). Gemini 3.5 Flash (GA; $1.50/$9.00 per M; rate limit figures not yet published). Gemini 3.5 Flash-Lite and Gemini 3.5 Flash Cyber launched July 2026; rate limit figures not yet published. Gemini 3.5 Pro remains in limited preview (2M context, Deep Think). Gemini 3.1 Pro remains available ($2/$12 per M ≤200K, $4/$18 >200K). Gemini 2.0 Flash/Flash-Lite shut down June 1, 2026. Docs
Groq: Free tier publishes exact numbers (30 RPM, 6K–30K TPM depending on model). Daily token budgets (TPD) alongside TPM. Cached tokens don’t count. Hosts Llama 4 Scout and other open models on free tier. Runs on custom LPU hardware. Docs
xAI (SpaceXAI): Current flagship is Grok 4.7 (September 21, 2026; grok-4.7; 500K context; $2/$6 per M below 200K prompt tokens, $4/$12 above; knowledge cutoff May 2026). Grok 4.6 is the previous flagship, still available ($2/$6 per M, same pricing structure; knowledge cutoff February 1, 2026). grok-build-0.1 is the agentic coding model ($1/$2 per M). 5-tier structure ($0/$50/$250/$1K/$5K thresholds) but numerical RPM/TPM only visible in xAI Console. Docs
Mistral: European data residency (GDPR). 5-tier structure (Free through Tier 4 at $500+). Limits enforced per RPS (not RPM), TPM, and tokens/month. Actual numbers require login at admin.mistral.ai. Mistral Large 4 (October 6, 2026; mistral-large-4; 1.05T total / 52B active plus 1.6B vision encoder; 1M context; public preview, not GA; per-token pricing not confirmed — do not quote one; licence not confirmed but described as open-weight). Mistral Medium 3.5 ($1.50/$7.50 per M) is the proprietary frontier tier. Mistral Large 3 (675B MoE, Apache 2.0, $0.50/$1.50 per M) and Mistral Small 4 (Apache 2.0, $0.15/$0.60 per M) are available. Devstral 2 ($0.40/$2.00 per M) available for coding workloads. Docs
DeepSeek: Fully dynamic concurrency limits based on server load. No published RPM/TPM. DeepSeek-V4.1-Flash (deepseek-flash) is the current flagship — 552B MoE with 8B active for input and 16B for output; native multimodal visual understanding; 1M context, 384K max output; pricing varies peak vs. off-peak: $0.30/$1.20 per M at peak, $0.15/$0.60 at off-peak (peak hours: 01:00–04:00 and 06:00–10:00 UTC, Monday–Friday, excluding Chinese public holidays) — always specify which rate you are quoting. The older deepseek-v4-flash and deepseek-v4-flash-vision-exp names are retired and route to V4.1-Flash. DeepSeek V4-Pro pricing is uncertain — a September 2026 announcement says V4-Pro traffic reroutes to V4.1-Flash at V4.1-Flash rates, but the live pricing page still lists V4-Pro separately; check both sources. V3.2 aliases deprecated July 24, 2026 — those endpoints are gone. Docs
Cerebras: Fastest inference (approximately 2,100 tok/s on Llama 4 Scout). Free tier: 30 RPM, 60K TPM, 1M TPD. Paid tier limits not publicly documented. Custom WSE-3 silicon. Docs
SambaNova: Best TTFT (approximately 0.2s). Free tier: 10–30 RPM depending on model size. Hosts up to Llama 4 Maverick for free. TPM and TPD limits not publicly documented. Custom RDU hardware. Docs
Together AI: Dynamic rate limits since January 2026. No fixed tiers or published numbers. Limits grow with sustained usage and are returned in API response headers. Docs
Fireworks AI: Dynamic ceiling up to 6,000 RPM (soft limit starts approximately 1 RPS, doubles hourly). On-demand GPU deployments remove limits. Spending tier caps: $50–$50K/month by tier. Docs
Cohere: Command A+ (May 20, 2026; Cohere’s first MoE, 218B total / 25B active; 128K input context and 64K max output; vision input, reasoning, translation, and agentic tasks; native citations; runs on 1x B200 or 2x H100; 48 languages including all official EU languages) is the flagship. Licence is unconfirmed — do not state Apache 2.0 or any other licence without checking Cohere’s model page. Self-hosting removes API rate limits entirely. API rate limit figures for Command A+ not yet published — 500 RPM (production chat) shown in tables is the Command R+ figure. Trial keys: 1,000 calls/month. No per-token API price published for Command A+. Docs
Perplexity: 6 tiers (T0–T5) based on cumulative spend. Leaky bucket algorithm. Deep Research model has very low limits (5–100 RPM). Agent API: 50–2,000 RPM by tier. Docs
Alibaba (Qwen): Qwen3.8-Max (August 3, 2026; 2.4T total / 95B active sparse MoE with hybrid attention; 1M context; 5th on Text Arena, 2nd on Vision Arena; weights now released as Qwen3.8-2.4T-A95B on Hugging Face and ModelScope — the first Qwen-Max-class model to ship openly) is the current flagship. Published per-token pricing not yet confirmed — write “not published” rather than guessing. Qwen3.8-27B (open-weight native multimodal dense, runs on consumer hardware) and Qwen3.8-Flash also released. Qwen3.7-Max (May 20; $2.50/$7.50 per M) is the previous flagship, still available. Open-weight family includes Qwen3.6 (Apache 2.0 — e.g., Qwen3.6-35B-A3B, Qwen3.6-27B). Region-specific limits apply — Beijing deployment is more generous than Singapore/Global. Qwen3.5 Flash at 30K RPM / 10M TPM (Beijing) is the highest confirmed throughput of any provider listed. Docs
Moonshot (Kimi): 6 tiers (T0–T5). T0 ($1 recharge): 3 RPM, 1 concurrent, 1.5M TPD. T5 ($3,000): 10K RPM, 1,000 concurrent, 5M TPM, unlimited TPD. Kimi K3 (2.8T parameters, 1M context, Opus-class performance at Sonnet-level pricing) is the current flagship — rate limit figures not yet confirmed in public documentation; K2.5 figures carried forward as a provisional floor. Automatic 75% caching discount applied without opt-in. Docs
Meta: Muse Wonder and Muse Wonder Full (October 2026) are Meta’s most capable models, built for personal and professional agentic tasks. Available to developers via the Meta Model API and Muse Code (Muse Wonder Full for Muse Code subscribers). No per-token pricing confirmed for either. Rate limit figures not yet published. Muse Spark 1.3 (long-horizon coding and agentic work) and Muse Spark 1.1 (July 2026) are previous-generation proprietary models. Llama 4 Scout (10M context) and Llama 4 Maverick (1M context) remain the open-weight family. Meta Model API
AWS Bedrock: Hosts Claude (Fable 5.1, Opus 5.5, Sonnet 5.5, Haiku 5.5, and legacy Claude models), Llama 4, Mistral with per-model per-region quotas. Amazon scaling back most Nova AI models (Premier, Omni, Reel, Canvas) while a new Frontier team works on a foundation model expected at re:Invent. 6 RPM per 1K TPM ratio. Provisioned Throughput removes limits. Docs
Azure AI: Hosts GPT-6 Astra, GPT-6.1 Sol, GPT-5.6 Sol (default in Microsoft 365 Copilot), GPT-5.5, GPT-5.4, Claude Fable 5.1/Opus 5.5/Sonnet 5.5, and Gemini 3.1 Pro across regions. Gemini 4 Argon, 3.8 Flash, 3.7 Flash, and 3.6 Flash availability on Azure not yet confirmed — verify model and region availability before planning deployments. PTU deployments remove per-request limits. Docs
NVIDIA NIM: Hosted API is for prototyping (40 RPM). Self-hosted NIM containers have no limits. Docs

Tips for managing rate limits

For a deep dive on token pricing, cost optimization strategies, caching mechanics, model routing architectures, and production cost modeling, see LLM Token Costs and Efficiency. This section covers rate limit management specifically.

Handling 429s

Use exponential backoff when you hit 429s. The Anthropic SDK, OpenAI SDK, and most third-party clients handle this automatically. Don’t build your own retry loop unless you need custom jitter or circuit-breaking behavior.

Check response headers before you hit the wall. Together AI and Fireworks return your current rate limit state in every API response. DeepSeek adjusts concurrency limits dynamically based on server load. Reading these headers in production enables proactive throttling rather than reactive retries.

GPT-4.1 Nano is shut down

GPT-4.1 Nano shut down October 23, 2026. Any pipeline referencing gpt-4.1-nano is now receiving errors — there is no grace period. GPT-6 Luna ($0.10/$0.50 per M) is OpenAI’s named replacement. GPT-5.4 Mini ($0.75/$4.50 per M) is an intermediate option if Luna is too stripped-down for a given workload.

GPT-4.1 and GPT-4.1 Mini: two months remaining

Both are still callable until January 14, 2027. If your pipeline depends on either, the migration window is approximately two months. GPT-6 Luna is the named replacement for both.

GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Luna: treat published limits as provisional

All three models are broadly available but their rate limit tier tables are not yet published. Figures in this post are carried forward from GPT-5.5. GPT-6 Astra runs $10/$50 per M; GPT-6.1 Sol runs $2/$10 per M; GPT-6 Luna runs $0.10/$0.50 per M. Check platform.openai.com/account/limits for your account’s actual current limits.

GPT-5.6 Sol repricing: update cost models

GPT-5.6 Sol dropped from $5/$30 to $4/$20 per M after the GPT-6 launch. GPT-5.5 is unchanged at $5/$30. Any cost model carrying the old $5/$30 figure for GPT-5.6 Sol needs revision.

Gemini 4 Argon introductory pricing expires in twenty days

Introductory pricing ($2/$10 per M) expires November 30, 2026. Standard rates ($4/$20) apply from January 1, 2027. Cost models projecting past November 30 must use the standard rate. The larger-prompt tier exists at $4/$20 but its exact token threshold is unconfirmed — do not quote a specific cutoff.

Gemini 3.8 / 3.7 / 3.6 Flash: six weeks to repricing

Introductory pricing ($0.75/$3.75 per M) expires December 31, 2026. Standard rate is $1.50/$7.50 from January 1, 2027. Any cost model using the introductory rate for dates past year-end is wrong.

Current Anthropic models: revise tokenizer math

The ~30%-more-tokens tokenizer arrived with the Claude 4.7 generation, not with Sonnet 5. Claude 4.7 and later all use it — that includes the entire current lineup (Fable 5.1, Opus 5.5, Sonnet 5.5, Haiku 5.5). A workload that consumed 20K ITPM on Sonnet 4.6 will consume approximately 26K ITPM on any current Claude model with the same inputs. Recheck limits against actual token counts, particularly at Tier 1 where ITPM is constrained at 30K (provisionally carried figure).

Anthropic adaptive thinking: no budget_tokens on current models

Extended thinking (thinking.type "enabled" plus budget_tokens) is deprecated on Opus 4.6 and Sonnet 4.6 and is NOT accepted on current models. Current models use adaptive thinking steered by the effort parameter. Code samples targeting Fable 5.1, Opus 5.5, Sonnet 5.5, or Haiku 5.5 must not include budget_tokens.

Caching for throughput (not just cost)

Prompt caching has a rate limit benefit separate from its cost benefit. The cost savings are covered in the token costs post. The rate limit implications:

Anthropic: Cached input tokens don’t count toward ITPM limits at all on Claude 4.x and 5.x models. With an 80% cache hit rate, a 2M ITPM limit effectively handles approximately 10M total input tokens per minute. Cache read multipliers differ by model: 0.025x input on Fable 5.1 ($0.25/M), 0.05x on Opus 5.5 ($0.20/M) and Sonnet 5.5 ($0.10/M), and 0.10x on everything else. Compute cache read costs from the verified input price rather than assuming a flat 10%.
Groq: Cached tokens don’t count toward TPM/TPD limits on the free tier, effectively expanding your daily token budget.
Moonshot (Kimi): Automatic 75% caching discount applied without opt-in. No cache management required.

DeepSeek V3.2 is gone; V4-Pro routing is uncertain

The July 24 deprecation deadline for V3.2 aliases has passed. If anything in your pipeline references a V3.2 alias, it is receiving errors. deepseek-flash is the current endpoint for V4.1-Flash. V4-Pro routing is uncertain — a September 2026 announcement says V4-Pro requests now route to V4.1-Flash, but the pricing page still lists V4-Pro separately. Check both sources before assuming V4-Pro pricing.

DeepSeek peak vs. off-peak pricing

DeepSeek-V4.1-Flash pricing varies by time of day. Peak ($0.30/$1.20 per M) applies during 01:00–04:00 and 06:00–10:00 UTC, Monday–Friday, excluding Chinese public holidays. Off-peak ($0.15/$0.60) applies at all other times. Always specify which rate you are quoting in cost models.

OpenAI Assistants API is deprecated

Deprecated August 2026. The Responses API is the replacement. Migration guidance is in OpenAI’s migration docs.

Batch APIs: higher queue limits

OpenAI, Anthropic, and Google all offer batch endpoints with queue limits that far exceed real-time TPM. For workloads that don’t need sub-second responses, batch endpoints let you move more tokens through tighter rate limits. See batch API cost savings for pricing details.

Model routing for rate limit distribution

Routing requests to different models by complexity distributes rate limit pressure across multiple buckets instead of concentrating it on your most constrained tier. A three-tier architecture (budget for triage, mid-tier for generation, flagship for reasoning) also cuts costs substantially. Full routing architecture with cost modeling is in the token costs post.

GPT-6 Luna ($0.10/$0.50 per M) and DeepSeek V4.1-Flash (from $0.15/$0.60 per M off-peak) are strong candidates for the triage and generation layers of a routing stack. Kimi K3 (Opus-class performance at Sonnet-level pricing) is worth evaluating as a reasoning layer once rate limit figures are confirmed. Claude Haiku 5.5 ($0.10/$0.50 per M for prompts under 100K tokens) is roughly 75% cheaper to run than Haiku 4.5 and is designed specifically for high-volume, latency-sensitive work like classification, extraction, and routing.

Custom silicon for fewer concurrent connections

Cerebras (approximately 2,100 tok/s) and SambaNova (approximately 0.2s TTFT) are faster than GPU-based providers by a large margin. A task that requires 10 parallel GPU-based API calls to meet a latency SLA might need 2–3 calls on Cerebras. Fewer concurrent calls means less rate limit pressure per unit of output.

Self-hosting as an escape hatch

Cohere’s Command A+ (218B MoE / 25B active) runs on 2x H100 or a single B200. Qwen3.8-Max (2.4T parameters, weights now publicly released as Qwen3.8-2.4T-A95B) and Kimi K3 (2.8T parameters) are also available for self-hosting at substantially higher hardware requirements. Mistral Large 4 (1.05T total / 52B active, open-weight, public preview) rounds out the open-weight options at the frontier tier. For teams already operating that hardware, self-hosting removes API rate limits entirely. The economics only work at scale — hardware cost needs to be weighed against API spend.

Watch for shared pools and hidden constraints

Fable 5.1 pool assignment is not yet formally documented. Check your Anthropic dashboard. Opus 5.5 pool assignment is not yet formally documented — Opus 4.8, 4.7, and 4.6 shared one rate limit bucket; check your dashboard for how the 5.x Opus line is bucketed. Sonnet 5.5 and Sonnet 5 likely share a pool — not formally confirmed; check your dashboard. Sending traffic to multiple model versions within the same pool draws from one shared bucket, not separate ones.