How does MiniMax M2 rank among AI models?
MiniMax M2 is a superseded version and is not on the current board as of 22 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
MiniMax·minimax/minimax-m2
MiniMax M2 is ModelCap archive rank #233 (Measured), from the ModelCap Index as of 22 Sept 2026, 02:49 UTC.
MiniMax M2 listed OpenRouter input price is $0.255 per 1M tokens and listed output price is $1.02 per 1M tokens, from OpenRouter listed prices as of 22 Sept 2026, 02:49 UTC.
MiniMax M2 has a published context limit of 205K tokens in the ModelCap catalogue as of 22 Sept 2026, 02:49 UTC.
MiniMax M2 has 3 published OpenRouter serving endpoints, from OpenRouter as of 22 Sept 2026, 02:49 UTC.
MiniMax M2 weight access is restricted license, from ModelCap classification of published repository metadata as of 22 Sept 2026, 02:49 UTC.
Snapshot facts · download the public dataset · methodology
ModelCap Index · All-versions archive
36.9#233
Measured · 55% support · score interval 31.3–42.5
Evidence as of 13 Sept 2026, 00:00 UTC
Superseded by MiniMax M3. It no longer holds a current-board position; its all-versions archive rank is #233.
Input
$0.255
per 1M tokens
Output
$1.02
per 1M tokens
Context
205K
tokens
Providers
3
endpoints
Gateway spend
—
latest · Vercel share
Providers
Uptime measured over the last 30 minutesHugging Face Inference Providers
Exact repository identityProvider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.
Reported evaluation leads (4)
Not independent measurementStructured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.
Other versions (5)
ModelCap Index · All-versions archive
Methodology36.9
Measured · 2 public benchmark observations across 2 boards
All-versions archive
#233
- Public rank basis
- Measured (measured)
- Index support
- 55.2% · strong
- Index interval
- 31.3–42.5
- Rank posterior
- Not available
- Top 5 / Top 10 probability
- Not available / Not available
- Posterior as of
- Snapshot timestamp unavailable
- Evidence as of
- 13 Sept 2026, 00:00 UTC
- Identity binding
- Exact catalogue product · minimax/minimax/minimax-m2/fp8 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata MiniMaxAI/MiniMax-M2@757303d492a50514c312788b5247a4f696a4c6a3 (not the evaluation revision)
- Index observations used
- 2
- Qualified Index evidence point
- 36.9
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
- 36.9
- Evidence status
- confirmed · 75% mass
- General preference
- 37.3
- Coding
- 33.3
- Agents & tools
- —
- Reasoning
- —
- Evidence breadth
- 92%
- Evidence coverage
- 55%
Market and catalogue signals · secondary, never the language Index rank
- Usage (OpenRouter popularity)
- 7.9
- Liquidity (providers × uptime)
- 99.5
- Open reach (HF downloads)
- —
- Surface (context / tools / modalities)
- 73.5
- Freshness
- 28.1
- · OpenRouter popularity #204
- · 3 live providers
- · Catalogue: context 204800, reasoning, tools
- · First seen 2025-10-23
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 Overall37.3
- Arena Coding33.3
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 index82.9
strong · 94% metadata coverage
- Artifact reproducibility
- 85.0
- Access & legal clarity
- 92.5
- Deployability
- 96.2
- Evaluation provenance
- 50.0
Missing: artifactReproducibility.base-lineage, evaluationProvenance.evaluation-dataset-revisions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market activity
Venue coverage- Market Gravity
- 38.1
- OpenRouter weekly popularity
- #204 of 322
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
- #214 of 402
- Rating
- 1345.9
- 95% confidence interval
- 1338–1354
- Votes
- 7K
- Source published at
- 13 Sept 2026, 00:00 UTC
- Category
- overall
- Identity match confidence
- 100%
Market Gravity breakdown
- Usage55%
- 7.9
- Liquidity25%
- 99.5
- Open reach15%
- 50.0
- Freshness5%
- 28.1
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
- Context window
- 205K tokens
- Max output
- 131K tokens
- Inputs
- Text
- Outputs
- Text
- Tokenizer
- Other
- Cached input tokens
- Not offered
- First seen on OpenRouter
- 23 Oct 2025
Capabilities
- Supported: Reasoning
- Supported: Tool use
- Supported: Structured output
- Supported: Response format
- Not supported: Moderated
Weights & access
Restricted license. Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment.
- Access
- Restricted license
- Licence
- modified-mit
- Pinned revision
- 757303d492a5
- Parameters
- 228.7B
- Architecture
- MiniMaxM2ForCausalLM
- Model type
- minimax_m2
- Hugging Face downloads (30d)
- 277K
- Downloads (all time)
- 2.8M
- Likes
- 2K
- Repository
- MiniMaxAI/MiniMax-M2
- Repository updated
- 23 Dec 2025, 08:37 UTC
Benchmark leaderboards featuring MiniMax M2
All leaderboardsMiniMax M2: common questions
How much does MiniMax M2 cost per 1M tokens?
MiniMax M2 is listed at $0.255 per 1M input tokens and $1.02 per 1M output tokens as of 22 September 2026 across 3 providers. 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 $1.02 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 MiniMax M2?
MiniMax M2 has a published context window of 205K tokens (204,800) and a maximum output of 131K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.
Is MiniMax M2 open-weight?
Restricted license (modified-mit). Downloadable weights use a model-specific or use-restricted license. Review the linked license before use, redistribution, or commercial deployment. The repository is MiniMaxAI/MiniMax-M2 on Hugging Face.
Which API providers serve MiniMax M2?
3 providers serve MiniMax M2 through OpenRouter as of 22 September 2026: Minimax, Google and Novita. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Which benchmarks has MiniMax M2 been evaluated on?
MiniMax M2 has published results on 4 public boards tracked by ModelCap as of 22 September 2026: Arena coding 1383 (#220 of 397), SWE-bench 61.0% (#24 of 47), AA τ²-Bench Telecom 86.8% (#87 of 436) and AA Humanity's Last Exam 13.7% (#234 of 615). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.
When was MiniMax M2 released?
MiniMax M2 first appeared in the catalogue on 23 Oct 2025. It has since been superseded by MiniMax M3. Rank and price movements since then are recorded on the site's changes feed.