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ModelCap

MiniMax M2.5

Arena #179Official publisher releaseRestricted license

MiniMax·#218 of 504 in the all-versions archive

MiniMax M2.5 is a language model from MiniMax. It ranks #218 of 504 in ModelCap's all-versions archive, with an Index score of 49.3, measured on 3 public benchmarks. Its score range of 44.5–54.1 spans positions #176–#241. It is listed at $0.27 per million input tokens and $0.95 per million output tokens across 6 providers. It reads up to 205K tokens of context, and its weights are downloadable under a use-restricted licence.

Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology

ModelCap Index · All-versions archive
49.3#218
Measured on 3 public benchmarks · range 44.5–54.1
Evidence as of 4 Nov 2026, 23:07 UTC
Market Gravity
40.8Increased by 0.4
Secondary market signal

Superseded by MiniMax M3. It no longer holds a current-board position; its all-versions archive rank is #218.

Input
$0.27
per 1M tokens
Output
$0.95
per 1M tokens
Context
205K
tokens
Providers
6
endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
VeniceCheapest$0.27$0.95198K—100.0%
StreamLake$0.27$1.08200K—100.0%
AtlasCloudfp8$0.295$1.20197Kfp8100.0%
DigitalOcean$0.30$1.2066K—100.0%
GMICloudfp8$0.30$1.20197Kfp8100.0%
Novitafp8$0.30$1.20205Kfp8100.0%

Hugging Face Inference Providers

Exact repository identity

Provider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.

ProviderInputOutputContextTTFTThroughputFeatures
novita
live
$0.30$1.20205K1029 ms44.5 tok/stools
featherless-ai
live
——————

Reported evaluation leads (11)

Not independent measurement

Structured 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.

Dataset / taskMetricValueRevisionProvenance
allenai/IFBench_test
prompt_level_loose
—70
Unpinned
not published
Reported
Quarantined
cais/hle
hle
—19.4
Unpinned
not published
Reported
Quarantined
collinear-ai/yc-bench
medium
—230,465
Unpinned
not published
Reported
Quarantined
Idavidrein/gpqa
diamond
—85.2
Unpinned
not published
Reported
Quarantined
internlm/WildClawBench
overall
—27.1
Unpinned
not published
Reported
Quarantined
internlm/WildClawBench
avg_time
—542
Unpinned
not published
Reported
Quarantined
internlm/WildClawBench
avg_cost
—9.6
Unpinned
not published
Reported
Quarantined
mercor/apex-agents
apex-agents
—6.2
Unpinned
not published
Reported
Quarantined
ScaleAI/SWE-bench_Pro
SWE_Bench_Pro
—55.4
Unpinned
not published
Reported
Quarantined
SWE-bench/SWE-bench_Verified
swe_bench_%_resolved
—75.8
Unpinned
not published
Reported
Quarantined
TIGER-Lab/MMLU-Pro
mmlu_pro
—80.1
Unpinned
not published
Reported
Quarantined

Other versions (5)

ModelCap Index · All-versions archive

Methodology
49.3
Measured on 3 public benchmarks
All-versions archive
#218 of 504
Score range
44.5–54.1
Rank range
#176–#241
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
65.6% · strong
Identity binding
Exact catalogue product · minimax/minimax/minimax-m2.5/fp8 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata MiniMaxAI/MiniMax-M2.5@2515a3ea0afec1dd22d0c7794b3a91557804d195 (not the evaluation revision)
Index observations used
3
Qualified Index evidence point
49.3
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
49.3
Evidence status
confirmed · 87% mass
General preference
49.9
Coding
51.6
Agents & tools
—
Reasoning
16.7
Evidence breadth
95%
Evidence coverage
66%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
11.8
Liquidity (providers × uptime)
99.8
Open reach (HF downloads)
—
Surface (context / tools / modalities)
73.5
Freshness
36.2
  • · OpenRouter popularity #170
  • · 6 live providers
  • · Catalogue: context 204800, reasoning, tools
  • · First seen 2026-02-12

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

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 index
88.8
strong · 94% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
92.5
Deployability
97.9
Evaluation provenance
76.9

Not yet published: the base model it derives from, 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
40.8
OpenRouter weekly popularity
#170 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
#179 of 419
Rating
1390.6
95% confidence interval
1387–1395
Votes
43K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
11.8

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
99.8

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
36.2

Time since first public availability, on a six-month half-life.

Specification

Model ID
minimax/minimax-m2.5
Context window
205K tokens
Declared output cap
33K 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
Outputs
Text
Tokenizer
Other
Cached input tokens
$0.03 / 1M
First seen on OpenRouter
12 Feb 2026

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
Pinned revision
2515a3ea0afe
Parameters
228.7B
Architecture
MiniMaxM2ForCausalLM
Model type
minimax_m2
Hugging Face downloads (30d)
1.3M
Downloads (all time)
6.6M
Likes
2K
Repository updated
26 Oct 2026, 07:08 UTC

Benchmark leaderboards featuring MiniMax M2.5

All leaderboards
Public benchmark boards on which MiniMax M2.5 has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)13911387–1395#179 of 419Not reported28 Oct 2026
Arena coding leaderboardArena (LMArena)14461440–1453#164 of 414Default28 Oct 2026
ARC-AGI-2 leaderboardARC Prize Foundation4.9%#186 of 280Default4 Nov 2026
SWE-bench leaderboardSWE-bench (Princeton / SWE-agent team)75.8%#2 of 47High17 Feb 2026
WildClawBench OpenClaw leaderboardWildClawBench27.1#32 of 34Default20 Jul 2026

MiniMax M2.5: common questions

How does MiniMax M2.5 rank among AI models?

MiniMax M2.5 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.

How much does MiniMax M2.5 cost per 1M tokens?

MiniMax M2.5 is listed at $0.27 per 1M input tokens and $0.95 per 1M output tokens as of 6 November 2026 across 6 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 M2.5?

MiniMax M2.5 has a published context window of 205K tokens (204,800). The snapshot lists a 32,768 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 MiniMax M2.5 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-M2.5 on Hugging Face.

Which API providers serve MiniMax M2.5?

6 providers serve MiniMax M2.5 through OpenRouter as of 6 November 2026: Venice, StreamLake, AtlasCloud, GMICloud, DigitalOcean and Novita. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has MiniMax M2.5 been evaluated on?

MiniMax M2.5 has published results on 5 public boards tracked by ModelCap as of 6 November 2026: Arena text 1391 (#179 of 419), Arena coding 1446 (#164 of 414), ARC-AGI-2 4.9% (#186 of 280), SWE-bench 75.8% (#2 of 47) and WildClawBench OpenClaw 27.1 (#32 of 34). 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 MiniMax M2.5 released?

MiniMax M2.5 first appeared in the catalogue on 12 Feb 2026. It has since been superseded by MiniMax M3. Rank and price movements since then are recorded on the site's changes feed.