How does GPT-5 Nano rank among AI models?
GPT-5 Nano is a superseded version and is not on the current board as of 6 November 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
GPT-5 Nano
Arena #239No linked weightsOpenAI·#305 of 504 in the all-versions archive
GPT-5 Nano is a language model from OpenAI. It ranks #305 of 504 in ModelCap's all-versions archive, with an Index score of 36.3, measured on 3 public benchmarks. Its score range of 31.1–41.5 spans positions #252–#347. It is listed at $0.05 per million input tokens and $0.40 per million output tokens across 2 providers. It reads up to 400K tokens of context, with no downloadable weights linked in the current source data.
Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology
ModelCap Index · All-versions archive
36.3#305
Measured on 3 public benchmarks · range 31.1–41.5
Evidence as of 4 Nov 2026, 23:07 UTC
Superseded by GPT-5.4 Nano. It no longer holds a current-board position; its all-versions archive rank is #305.
Input
$0.05
per 1M tokens
Output
$0.40
per 1M tokens
Context
400K
tokens
Providers
2
4 endpoints
Providers
Uptime measured over the last 30 minutesReasoning efforts
Best supported result can inform ModelCapPublished Max, X-High, High and other configurations for this model. These are sourced scores, not head-to-head essays.
Related community configurations
Human preference ratingOther versions (2)
ModelCap Index · All-versions archive
Methodology36.3
Measured on 3 public benchmarks
All-versions archive
#305 of 504
- Score range
- 31.1–41.5
- Rank range
- #252–#347
- Evidence as of
- 4 Nov 2026, 23:07 UTC
- Benchmarks used
- ARC-AGI-2 Verified, Arena Coding, Arena Overall
Technical details
- Public rank basis
- Measured (measured)
- Evidence label
- Measured · 3 public benchmark observations across 3 boards
- Index support
- 60.2% · strong
- Identity binding
- Exact catalogue product · openai/openai/gpt-5-nano · aggregates disclosed benchmark configurations · endpoint configuration not claimed
- Index observations used
- 3
- Qualified Index evidence point
- 36.3
Bayesian Evidence Score · measured evidence input only
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
- Observed capability
- 36.3
- Evidence status
- confirmed · 85% mass
- General preference
- 36.9
- Coding
- 37.9
- Agents & tools
- —
- Reasoning
- 14.0
- Evidence breadth
- 95%
- Evidence coverage
- 60%
Market and catalogue signals · secondary, never the language Index rank
- Usage (OpenRouter popularity)
- 18.1
- Liquidity (providers × uptime)
- 98.1
- Open reach (HF downloads)
- —
- Surface (context / tools / modalities)
- 93.3
- Freshness
- 17.6
- · OpenRouter popularity #118
- · 2 live providers
- · Catalogue: context 400000, reasoning, tools, modalities Text/Image/File
- · First seen 2025-08-07
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
BES evidence selected · measured input only
- Arena Overall · High36.9
- Arena Coding · High37.9
- ARC-AGI-2 Verified · High14.0
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Deployment readiness
Metadata index48.0
partial · 56% metadata coverage
- Artifact reproducibility
- 0.0
- Access & legal clarity
- 30.3
- Deployability
- 90.0
- Evaluation provenance
- 74.6
Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, pinned evaluation dataset versions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market activity
Venue coverage- Market Gravity
- 42.9
- OpenRouter weekly popularity
- #118 of 339
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
Arena preference
- Status
- Ranked
- Source
- LMArena
- Official rank
- #239 of 419
- Rating
- 1337.7
- 95% confidence interval
- 1331–1345
- Votes
- 8K
- Source published at
- 28 Oct 2026, 00:00 UTC
- Category
- overall
- Identity match confidence
- 100%
Market Gravity breakdown
- Usage55%
- 18.1
- Liquidity25%
- 98.1
- Open reach15%
- 50.0
- Freshness5%
- 17.6
OpenRouter weekly popularity across the full model catalogue.
Independent providers versus the model's open or closed cohort, weighted by uptime.
Hugging Face 30-day downloads for open models; neutral for closed models.
Time since first public availability, on a six-month half-life.
Specification
- Model ID
openai/gpt-5-nano- Context window
- 400K tokens
- Declared output cap
- 128K tokens
OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
- Inputs
- Text, Image, File
- Outputs
- Text
- Tokenizer
- GPT
- Cached input tokens
- $0.0050 / 1M
- First seen on OpenRouter
- 7 Aug 2025
- Knowledge cutoff
- 2024-05-31
Capabilities
- Supported: Reasoning
- Supported: Tool use
- Supported: Structured output
- Supported: Response format
- Supported: Moderated
Benchmark leaderboards featuring GPT-5 Nano
All leaderboardsGPT-5 Nano: common questions
How much does GPT-5 Nano cost per 1M tokens?
GPT-5 Nano is listed at $0.05 per 1M input tokens and $0.40 per 1M output tokens as of 6 November 2026; the lowest output price among 2 providers is $0.20 on OpenAI. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.30 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
What is the context window of GPT-5 Nano?
GPT-5 Nano has a published context window of 400K tokens (400,000). The snapshot lists a 128,000 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.
Is GPT-5 Nano open-weight?
No linked weights. No downloadable model weights are linked in the current source data. This does not identify every API or chat product that offers the model.
Which API providers serve GPT-5 Nano?
2 providers serve GPT-5 Nano through OpenRouter as of 6 November 2026: OpenAI and Azure. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Which benchmarks has GPT-5 Nano been evaluated on?
GPT-5 Nano has published results on 3 public boards tracked by ModelCap as of 6 November 2026: Arena text 1338 (#239 of 419), Arena coding 1385 (#233 of 414) and ARC-AGI-2 2.6% (#209 of 280). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.
When was GPT-5 Nano released?
GPT-5 Nano first appeared in the catalogue on 7 Aug 2025, with a published knowledge cutoff of 2024-05-31. It has since been superseded by GPT-5.4 Nano. Rank and price movements since then are recorded on the site's changes feed.