How does MiniMax M1 40k rank among AI models?
MiniMax M1 40k is a superseded version and is not on the current board as of 13 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
MiniMaxAI·MiniMaxAI/MiniMax-M1-40k
MiniMax M1 40k is ModelCap archive rank #142 (Modeled · peer benchmarks), from the ModelCap Index as of 13 Sept 2026, 14:40 UTC.
MiniMax M1 40k weight access is open weights, from ModelCap classification of published repository metadata as of 13 Sept 2026, 14:40 UTC.
Snapshot facts · download the public dataset · methodology
ModelCap Index · All-versions archive
49.9#142
Estimated · 36% support · score interval 37.2–62.6
No admitted evaluation publication timestamp yet
Superseded by MiniMax M1 80k. It no longer holds a current-board position; its all-versions archive rank is #142.
OpenRouter endpoint status could not be refreshed. This model is not treated as currently served until a successful observation arrives.
Input
Self-hosted
weights only · no listed API price
Output
Self-hosted
weights only · no listed API price
Context
—
tokens
Providers
0
endpoints
Gateway spend
—
latest · Vercel share
Providers
Uptime measured over the last 30 minutesCurrent provider status is unavailable.
Reported evaluation leads (1)
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. Rows marked as used were laddered against independently measured peers inside the launch-card channel of this model's modeled placement, with the replay-measured optimism haircut applied; the others played no part.
Other versions (1)
ModelCap Index · All-versions archive
Methodology49.9
Modeled · peer benchmarks · calibrated architecture-and-release-era fallback from static public metadata
All-versions archive
#142
- Public rank basis
- Modeled · peer benchmarks (architecture)
- Index support
- 36.0% · limited
- Index interval
- 37.2–62.6
- Rank posterior
- Not available
- Top 5 / Top 10 probability
- Not available / Not available
- Posterior as of
- Snapshot timestamp unavailable
- Evidence as of
- No admitted evaluation publication timestamp
- Identity binding
- Exact catalogue product · minimaxai/MiniMaxAI/MiniMax-M1-40k · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata MiniMaxAI/MiniMax-M1-40k@2d1d1c2f00c97fc1245bfce7648649b76e0a8e6e (not the evaluation revision)
- Index observations used
- 0
- Qualified Index evidence point
- 49.9
How this position was produced · fused launch placement
No general-family board lists this model yet. Its point estimate is the precision-weighted mean of every channel that spoke for it; each channel’s share is the weight it carried. Independent measurements replace this placement as boards list the model.
- Fused estimate
- 49.9 ± 9.9
- Independent share
- 0%
- Shrink toward corpus
- +0.6
- Peer ceiling share
- 11%
- Optimism haircut
- None required · cross lab probe, 7 probes
- Method
- precision-weighted-v1
- · Launch card row aime-2024: inside the resolved peer range
- · Launch card row aime-2025: inside the resolved peer range
- · Launch card row gpqa-diamond: claims below every resolved peer
- · Launch card row hle-without-tools: claims below every resolved peer
- · Launch card row livecodebench: inside the resolved peer range
- · Launch card row math-500: claims below every resolved peer
- · Launch card row mmlu-pro: claims below every resolved peer
- · Launch card row swe-bench-verified: inside the resolved peer range
- · Launch card row tau-bench: claims above every resolved peer
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
- —
- Evidence status
- No admitted measured evidence
- General preference
- —
- Coding
- —
- Agents & tools
- —
- Reasoning
- —
- Evidence breadth
- 0%
- Evidence coverage
- 0%
Market and catalogue signals · secondary, never the language Index rank
- Usage (OpenRouter popularity)
- —
- Liquidity (providers × uptime)
- —
- Open reach (HF downloads)
- 77.7
- Surface (context / tools / modalities)
- 0.0
- Freshness
- 17.0
- · HF 30d downloads 6280
- · Catalogue surface
- · First seen 2025-06-05
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
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.
Experimental capability estimate
Estimate policy48.0
29.8–66.2 uncertainty interval
- Confidence
- 69%
- Training support
- 192 models · 109 lineages
- Out-of-domain check
- in domain
- Feature coverage
- 71%
- Lineage-held-out error
- 10.1 MAE
Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.
Deployment readiness
Metadata index47.9
partial · 52% metadata coverage
- Artifact reproducibility
- 85.0
- Access & legal clarity
- 100.0
- Deployability
- 8.0
- Evaluation provenance
- 0.0
Missing: artifactReproducibility.base-lineage, deployability.independent-provider-records, deployability.measured-provider-uptime, deployability.published-provider-pricing, deployability.declared-capacity, evaluationProvenance.admitted-evaluation-observations, evaluationProvenance.capability-family-breadth, evaluationProvenance.evaluation-source-diversity, evaluationProvenance.identity-and-source-confidence, 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
- 12.5
- OpenRouter weekly popularity
- Not listed
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
No matched Arena rating
This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.
Market Gravity breakdown
- Usage55%
- 0.0
- Liquidity25%
- 0.0
- Open reach15%
- 77.7
- Freshness5%
- 17.0
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
- — tokens
- Max output
- —
- Inputs
- Text
- Outputs
- Text
- Tokenizer
- —
- Cached input tokens
- Not offered
- First seen on OpenRouter
- 5 Jun 2025
Capabilities
- Not supported: Reasoning
- Not supported: Tool use
- Not supported: Structured output
- Not supported: Response format
- Not supported: Moderated
Weights & access
Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.
- Access
- Open weights
- Licence
- apache-2.0
- Pinned revision
- 2d1d1c2f00c9
- Parameters
- 456.1B
- Architecture
- MiniMaxM1ForCausalLM
- Model type
- minimax_m1
- Hugging Face downloads (30d)
- 6K
- Downloads (all time)
- 335K
- Likes
- 185
- Repository
- MiniMaxAI/MiniMax-M1-40k
- Repository updated
- 7 Jul 2025, 07:50 UTC
Benchmark leaderboards featuring MiniMax M1 40k
All leaderboardsMiniMax M1 40k: common questions
How much does MiniMax M1 40k cost per 1M tokens?
No live API price is listed for MiniMax M1 40k in the current snapshot as of 13 September 2026 because the latest endpoint refresh was unavailable. ModelCap shows a price only when a provider currently lists one.
Is MiniMax M1 40k open-weight?
Open weights (apache-2.0). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is MiniMaxAI/MiniMax-M1-40k on Hugging Face.
Which benchmarks has MiniMax M1 40k been evaluated on?
MiniMax M1 40k has published results on 2 public boards tracked by ModelCap as of 13 September 2026: AA τ²-Bench Telecom 31.6% (#265 of 436) and AA Humanity's Last Exam 7.8% (#316 of 605). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.
When was MiniMax M1 40k released?
MiniMax M1 40k first appeared in the catalogue on 5 Jun 2025. It has since been superseded by MiniMax M1 80k. Rank and price movements since then are recorded on the site's changes feed.