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BenchLM
Anthropic logo
Model A
Claude Opus 4.5

Anthropic

63.91/100

Supported · Public rank #46

90% interval 49.9–77.9

Claude Opus 4.5 vs MiniMax M3

Updated August 30, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

MiniMax logo
Model B
MiniMax M3

MiniMax

68.73/100

Supported · Public rank #21

90% interval 63.5–74.0

Decision reading

MiniMax M3 has the higher public score estimate, 68.73 versus 63.91, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

9 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Coding work

    Code generation, repair, and software-engineering tasks

    MiniMax M3

    MiniMax M3 leads on the same 2 weighted benchmark rows.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    MiniMax M3

    MiniMax M3 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    MiniMax M3

    MiniMax M3 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.

    Confidence: limited

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Claude Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
9
Claude Opus 4.5 only
36
MiniMax M3 only
13
Like-for-like categories
1 / 8

2 categories use different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Coding

Like-for-like
Claude Opus 4.5
71.7
MiniMax M3
72.2
Weighted basis
2 vs 2 rows
Reading
MiniMax M3 leads

Agentic

Directional only
Claude Opus 4.5
62.6
MiniMax M3
72.3
Weighted basis
2 vs 3 rows
Reading
Directional only

Multimodal

Directional only
Claude Opus 4.5
69.9
MiniMax M3
64.9
Weighted basis
2 vs 2 rows
Reading
Directional only

Reasoning

Not comparable
Claude Opus 4.5
64.4
MiniMax M3
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Claude Opus 4.5
58.1
MiniMax M3
Not measured
Weighted basis
4 vs 0 rows
Reading
Not comparable

Math

Not comparable
Claude Opus 4.5
57.5
MiniMax M3
85.7
Weighted basis
4 vs 1 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.5
85.7
MiniMax M3
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 4.5
69.5
MiniMax M3
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Claude Opus 4.5
$0.0175
Fits in one request
MiniMax M3
$0.0009
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.5
$0.325
Fits in one request
MiniMax M3
$0.0186
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Claude Opus 4.5
$1.35
Does not fit in one request
Cached input priced at the published list-input rate
MiniMax M3
$0.03
Fits in one request

Claude Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Context window

Maximum documented context; output-token limits may be lower.

Claude Opus 4.5

200K

MiniMax M3

1M

API model ID

Claude Opus 4.5

Not sourced

MiniMax M3

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Opus 4.5

Not published

MiniMax M3

$0.06 per 1M cached input tokens

Documented inputs

Claude Opus 4.5

Not sourced

MiniMax M3

Not sourced

Documented outputs

Claude Opus 4.5

Not sourced

MiniMax M3

Not sourced

Provider availability

Claude Opus 4.5

Not sourced

MiniMax M3

Not sourced

Reasoning profile

Claude Opus 4.5

Non-Reasoning

MiniMax M3

Non-Reasoning

Weight access

Claude Opus 4.5

Proprietary

MiniMax M3

Open Weight

License

Claude Opus 4.5

Proprietary

MiniMax M3

Open Weight

Release date

Claude Opus 4.5

2025-11-01

MiniMax M3

2026-06-01

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
MiniMax M3 has the higher public score estimate, 68.73 versus 63.91, but the 90% score intervals overlap.
Workload cost
Repository review: $0.325 vs $0.0186. Cache-heavy agent loop: $1.35 vs $0.03.
Context tradeoff
MiniMax M3 has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence58 rows

Agentic

  • Terminal-Bench 2.0

    Claude Opus 4.559.3%
    Source
    MiniMax M366%
    Source

    MiniMax M3 leads this result

  • OSWorld-Verified

    Claude Opus 4.566.3%
    Source
    MiniMax M370.1%
    Source

    MiniMax M3 leads this result

  • OSWorld

    Claude Opus 4.566.3%
    Source
    MiniMax M3—

    Not directly comparable

  • Claw-Eval

    Claude Opus 4.559.6%
    Source
    MiniMax M374.5%
    Source

    MiniMax M3 leads this result

  • QwenClawBench

    Claude Opus 4.552.3%
    Source
    MiniMax M3—

    Not directly comparable

  • τ³-bench results

    Claude Opus 4.570.2%
    Source
    MiniMax M3—

    Not directly comparable

  • VITA-Bench

    Claude Opus 4.523.3%
    Source
    MiniMax M3—

    Not directly comparable

  • DeepPlanning

    Claude Opus 4.526.4%
    Source
    MiniMax M3—

    Not directly comparable

  • Toolathlon

    Claude Opus 4.543.5%
    Source
    MiniMax M3—

    Not directly comparable

  • MCP Atlas

    Claude Opus 4.542.3%
    Source
    MiniMax M374.2%
    Source

    MiniMax M3 leads this result

  • MCP-Tasks

    Claude Opus 4.571.8%
    Source
    MiniMax M3—

    Not directly comparable

  • WideResearch

    Claude Opus 4.576.4%
    Source
    MiniMax M3—

    Not directly comparable

  • CyberGym

    Claude Opus 4.550.6%
    Source
    MiniMax M3—

    Not directly comparable

  • Gert Labs

    Claude Opus 4.564.23%
    Source
    MiniMax M3—

    Not directly comparable

  • JobBench

    Claude Opus 4.532.3%
    Source
    MiniMax M3—

    Not directly comparable

  • BrowseComp

    Claude Opus 4.5—
    MiniMax M383.5%
    Source

    Not directly comparable

  • BankerToolBench

    Claude Opus 4.5—
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    Claude Opus 4.5—
    MiniMax M319.8%
    Source

    Not directly comparable

  • OSWorld 2.0

    Claude Opus 4.5—
    MiniMax M34.6%
    Source

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Opus 4.580.9%
    Source
    MiniMax M380.5%
    Source

    Claude Opus 4.5 leads this result

  • LiveCodeBench v6

    Claude Opus 4.584.8%
    Source
    MiniMax M3—

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.557.1%
    Source
    MiniMax M359%
    Source

    MiniMax M3 leads this result

  • SWE Multilingual

    Claude Opus 4.577.5%
    Source
    MiniMax M3—

    Not directly comparable

  • NL2Repo

    Claude Opus 4.543.2%
    Source
    MiniMax M342.1%
    Source

    Claude Opus 4.5 leads this result

  • Terminal-Bench 2.0

    Claude Opus 4.5—
    MiniMax M366.0%
    Source

    Not directly comparable

  • VIBE V2

    Claude Opus 4.5—
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    Claude Opus 4.5—
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    Claude Opus 4.5—
    MiniMax M328.8%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Claude Opus 4.5—
    MiniMax M348.4%
    Source

    Not directly comparable

Reasoning

  • LongBench v2

    Claude Opus 4.564.4%
    Source
    MiniMax M3—

    Not directly comparable

  • AI-Needle

    Claude Opus 4.574%
    Source
    MiniMax M3—

    Not directly comparable

Knowledge

  • GPQA

    Claude Opus 4.587%
    Source
    MiniMax M3—

    Not directly comparable

  • SuperGPQA

    Claude Opus 4.570.6%
    Source
    MiniMax M3—

    Not directly comparable

  • MMLU-Pro

    Claude Opus 4.589.5%
    Source
    MiniMax M3—

    Not directly comparable

  • MMLU-Redux

    Claude Opus 4.596.6%
    Source
    MiniMax M3—

    Not directly comparable

  • C-Eval

    Claude Opus 4.592.2%
    Source
    MiniMax M3—

    Not directly comparable

  • HLE

    Claude Opus 4.530.8%
    Source
    MiniMax M3—

    Not directly comparable

Math

  • AIME26

    Claude Opus 4.595.1%
    Source
    MiniMax M3—

    Not directly comparable

  • HMMT Feb 2025

    Claude Opus 4.592.9%
    Source
    MiniMax M3—

    Not directly comparable

  • HMMT Nov 2025

    Claude Opus 4.593.3%
    Source
    MiniMax M3—

    Not directly comparable

  • HMMT Feb 2026

    Claude Opus 4.585.3%
    Source
    MiniMax M3—

    Not directly comparable

  • MMAnswerBench

    Claude Opus 4.584.0%
    Source
    MiniMax M3—

    Not directly comparable

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 4.520.690%
    Source
    MiniMax M3—

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 4.54.167%
    Source
    MiniMax M3—

    Not directly comparable

  • USAMO 2026

    Claude Opus 4.5—
    MiniMax M385.7%
    Source

    Not directly comparable

Multilingual

  • MMLU-ProX

    Claude Opus 4.585.7%
    Source
    MiniMax M3—

    Not directly comparable

  • NOVA-63

    Claude Opus 4.556.7%
    Source
    MiniMax M3—

    Not directly comparable

Multimodal

  • MMMU-Pro

    Claude Opus 4.570.6%
    Source
    MiniMax M378.1%
    Source

    MiniMax M3 leads this result

  • MathVision

    Claude Opus 4.574.3%
    Source
    MiniMax M3—

    Not directly comparable

  • CharXiv

    Claude Opus 4.568.5%
    Source
    MiniMax M3—

    Not directly comparable

  • VideoMMMU

    Claude Opus 4.584.4%
    Source
    MiniMax M384.6%
    Source

    MiniMax M3 leads this result

  • ScreenSpot Pro

    Claude Opus 4.545.7%
    Source
    MiniMax M3—

    Not directly comparable

  • V*

    Claude Opus 4.567.0%
    Source
    MiniMax M3—

    Not directly comparable

  • OfficeQA Pro

    Claude Opus 4.5—
    MiniMax M345.1%
    Source

    Not directly comparable

  • OmniDocBench 1.5

    Claude Opus 4.5—
    MiniMax M391.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Claude Opus 4.5—
    MiniMax M385.4%
    Source

    Not directly comparable

Instruction following

  • IFEval

    Claude Opus 4.590.9%
    Source
    MiniMax M3—

    Not directly comparable

  • IFBench

    Claude Opus 4.558%
    Source
    MiniMax M3—

    Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.5 or MiniMax M3?

MiniMax M3 has the higher public score estimate, 68.73 versus 63.91, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Opus 4.5 or MiniMax M3?

MiniMax M3 leads the like-for-like coding comparison across 2 shared weighted benchmark rows.

Which is better for agentic tasks, Claude Opus 4.5 or MiniMax M3?

The current agentic tasks averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Claude Opus 4.5 or MiniMax M3?

For the stated presets, chat costs $0.0175 on Claude Opus 4.5 and $0.0009 on MiniMax M3; repository review costs $0.325 and $0.0186; the cache-heavy agent loop costs $1.35 and $0.03. Claude Opus 4.5 does not fit this workload in one request. Claude Opus 4.5 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Opus 4.5 or MiniMax M3?

MiniMax M3 has the larger documented context window: 1M, compared with 200K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 30, 2026

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