Model A

Anthropic

72.33/100

Supported · Public rank #17

90% interval 60.4–84.3

Claude Opus 4.7 vs MiniMax M3

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

Model B

MiniMax M3

MiniMax

68.73/100

Supported · Public rank #21

90% interval 63.5–74.0

Decision reading

Claude Opus 4.7 has the higher public score estimate, 72.33 versus 68.73, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

2 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.

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
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
MiniMax M3
MiniMax M3 has the lower estimated token cost for this stated workload. Claude Opus 4.7 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback

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
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Long documents
Prompts that approach the documented context limit
No clear pick
The documented context windows are equal.
Confidence: documented

What is actually comparable

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

6 Claude Opus 4.7 only

2 Shared

20 MiniMax M3 only

Shared results: 2
Claude Opus 4.7 only: 6
MiniMax M3 only: 20
Like-for-like categories: 0 / 8

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.

Agentic

Not comparable

Claude Opus 4.7: Not measured
MiniMax M3: 72.3
Weighted basis: 0 vs 3 rows
Reading: Not comparable

Coding

Not comparable

Claude Opus 4.7: Not measured
MiniMax M3: 72.2
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Reasoning

Not comparable

Claude Opus 4.7: Not measured
MiniMax M3: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Knowledge

Not comparable

Claude Opus 4.7: Not measured
MiniMax M3: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Math

Not comparable

Claude Opus 4.7: 38.6
MiniMax M3: 85.7
Weighted basis: 2 vs 1 rows
Reading: Not comparable

Multilingual

Not comparable

Claude Opus 4.7: Not measured
MiniMax M3: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Multimodal

Not comparable

Claude Opus 4.7: Not measured
MiniMax M3: 64.9
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Instruction following

Not comparable

Claude Opus 4.7: Not measured
MiniMax M3: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Claude Opus 4.7 and MiniMax M3
Category	Claude Opus 4.7	MiniMax M3	Weighted basis	Reading
Agentic	Not measured	72.3	Not comparable0 vs 3 rows	Not comparable
Coding	Not measured	72.2	Not comparable0 vs 2 rows	Not comparable
Reasoning	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Knowledge	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Math	38.6	85.7	Not comparable2 vs 1 rows	Not comparable
Multilingual	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Multimodal	Not measured	64.9	Not comparable0 vs 2 rows	Not comparable
Instruction following	Not measured	Not measured	Not comparable0 vs 0 rows	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.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

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 4.7: $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 4.7: $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 4.7: $1.35; Fits in one request; Cached input priced at the published list-input rate
MiniMax M3: $0.03; Fits in one request

MiniMax M3 has the lower modeled cost

Claude Opus 4.7 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.

SpecificationClaude Opus 4.7MiniMax M3

Claude Opus 4.7

Non-Reasoning

MiniMax M3

Non-Reasoning

Weight access

Claude Opus 4.7

Proprietary

MiniMax M3

Open Weight

License

Claude Opus 4.7

Proprietary

MiniMax M3

Open Weight

Release date

Claude Opus 4.7

2026-04-16

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: Claude Opus 4.7 has the higher public score estimate, 72.33 versus 68.73, 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: Both models list 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 evidence28 rows

Agentic

Gert Labs
Claude Opus 4.765.59%
Source
MiniMax M3—
Not directly comparable
ResearchClawBench
Shared source
Claude Opus 4.720.7%
MiniMax M319.8%
Claude Opus 4.7 leads this result
OSWorld 2.0
Shared source
Claude Opus 4.713.9%
MiniMax M34.6%
Claude Opus 4.7 leads this result
Terminal-Bench 2.0
Claude Opus 4.7—
MiniMax M366%
Source
Not directly comparable
BrowseComp
Claude Opus 4.7—
MiniMax M383.5%
Source
Not directly comparable
OSWorld-Verified
Claude Opus 4.7—
MiniMax M370.1%
Source
Not directly comparable
MCP Atlas
Claude Opus 4.7—
MiniMax M374.2%
Source
Not directly comparable
Claw-Eval
Claude Opus 4.7—
MiniMax M374.5%
Source
Not directly comparable
BankerToolBench
Claude Opus 4.7—
MiniMax M376.1%
Source
Not directly comparable

Coding

Vibe Code Bench
Claude Opus 4.771.00%
Source
MiniMax M3—
Not directly comparable
React Native Evals
Claude Opus 4.782.8%
Source
MiniMax M3—
Not directly comparable
FrontierCode 1.1 Main
Claude Opus 4.738.5%
Source
MiniMax M3—
Not directly comparable
SWE-bench Verified
Claude Opus 4.7—
MiniMax M380.5%
Source
Not directly comparable
SWE-bench Pro
Claude Opus 4.7—
MiniMax M359%
Source
Not directly comparable
Terminal-Bench 2.0
Claude Opus 4.7—
MiniMax M366.0%
Source
Not directly comparable
NL2Repo
Claude Opus 4.7—
MiniMax M342.1%
Source
Not directly comparable
VIBE V2
Claude Opus 4.7—
MiniMax M350.1%
Source
Not directly comparable
SVG-Bench
Claude Opus 4.7—
MiniMax M363.7%
Source
Not directly comparable
KernelBench Hard
Claude Opus 4.7—
MiniMax M328.8%
Source
Not directly comparable
OpenHarmony Bench
Claude Opus 4.7—
MiniMax M348.4%
Source
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
Claude Opus 4.743.793%
Source
MiniMax M3—
Not directly comparable
FrontierMath v2 (Tier 4)
Claude Opus 4.722.917%
Source
MiniMax M3—
Not directly comparable
USAMO 2026
Claude Opus 4.7—
MiniMax M385.7%
Source
Not directly comparable

Multimodal

OfficeQA Pro
Claude Opus 4.7—
MiniMax M345.1%
Source
Not directly comparable
OmniDocBench 1.5
Claude Opus 4.7—
MiniMax M391.6%
Source
Not directly comparable
MMMU-Pro
Claude Opus 4.7—
MiniMax M378.1%
Source
Not directly comparable
VideoMMMU
Claude Opus 4.7—
MiniMax M384.6%
Source
Not directly comparable
Video-MME (with subtitle)
Claude Opus 4.7—
MiniMax M385.4%
Source
Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.7 or MiniMax M3?

Claude Opus 4.7 has the higher public score estimate, 72.33 versus 68.73, 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 4.7 or MiniMax M3?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Claude Opus 4.7 or MiniMax M3?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Claude Opus 4.7 or MiniMax M3?

For the stated presets, chat costs $0.0175 on Claude Opus 4.7 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 4.7 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Opus 4.7 or MiniMax M3?

Both models list the same context window, 1M.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 30, 2026

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Claude Opus 4.7 vs MiniMax M3

Which one for your work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Coding work

Agentic work

Long documents

What is actually comparable

Category results, on a stated basis

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Benchmark evidence

Agentic

Coding

Math

Multimodal

Frequently asked questions

Which is better, Claude Opus 4.7 or MiniMax M3?

Which is better for coding, Claude Opus 4.7 or MiniMax M3?

Which is better for agentic tasks, Claude Opus 4.7 or MiniMax M3?

Which costs less, Claude Opus 4.7 or MiniMax M3?

Which has the larger context window, Claude Opus 4.7 or MiniMax M3?

Related comparisons

Watch Claude Opus 4.7 vs MiniMax M3