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BenchLM

Claude Sonnet 5.5 vs MiniMax M3

Updated September 28, 2026. Rank says Claude Sonnet 5.5 is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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Decision reading

Claude Sonnet 5.5 has the higher public score, 80.49 versus 54.78, and the 90% score intervals do not overlap. 2 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A
Anthropic logo
Claude Sonnet 5.5

Anthropic

80.49/100

Estimated · Public rank #5

90% interval 69.0–92.0

Model B
MiniMax logo
MiniMax M3

MiniMax

54.78/100

Supported · Public rank #59

90% interval 46.2–63.4

Shared results
2
Claude Sonnet 5.5 only
45
MiniMax M3 only
25
Like-for-like categories
2 / 8
Estimated: Claude Sonnet 5.5 · Supported: MiniMax M3How the comparison works

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.

  • Agentic work

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

    Claude Sonnet 5.5

    Claude Sonnet 5.5 leads on the public agentic lane, 66.1 to 39.7, with Supported evidence for both models and non-overlapping 90% intervals.

    Confidence: stronger

  • 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. 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

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    Claude Sonnet 5.5 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

Which one for a specific job

Choose a job from the LLM Selector's task catalog to see the category row it rests on, under the same basis rules as the table below. A directional row stays directional; choosing a job never creates a winner.

The same task catalog as the LLM Selector. Each job names the evidence surface it rests on; nothing here adds a new score.

79.6Claude Sonnet 5.538.7MiniMax M3

Directional only · BenchAlign v5.7

Claude Sonnet 5.5 scores higher, but at least one score rests on Estimated evidence or a different benchmark set. Directional only, no winner.

Coding scores combine specific tasks and setups. Match the editor, harness, and effort to your workflow.

Open the coding leaderboardShortlist models for this job
Same basis rules as the category table below

What is actually comparable

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

2 categories rest on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

Bars run 0–100 on each benchmark’s normalized display scale

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.7 lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Like-for-like
Claude Sonnet 5.5
66.1
Supported · #10/111
MiniMax M3
39.7
Supported · #52/111
Basis
BenchAlign v5.7 lane · 11 vs 9 public rows
Reading
Claude Sonnet 5.5 leads

Knowledge

Like-for-like
Claude Sonnet 5.5
80.9
Supported · #6/160
MiniMax M3
48.3
Supported · #63/160
Basis
BenchAlign v5.7 lane · 16 vs 2 public rows
Reading
Claude Sonnet 5.5 leads

Coding

Directional only
Claude Sonnet 5.5
79.6
Estimated · #3/136
MiniMax M3
38.7
Supported · #59/136
Basis
BenchAlign v5.7 lane · 9 vs 10 public rows
Reading
Directional only

Reasoning

Directional only
Claude Sonnet 5.5
79.2
#7/27
MiniMax M3
79.4
#5/27
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Directional only

Multimodal

Not comparable
Claude Sonnet 5.5
83.3
Unranked · 7 rankable rows
MiniMax M3
52.0
#37/50
Basis
Provisional lane · 1 vs 2 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Sonnet 5.5
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Sonnet 5.5
Not ranked
MiniMax M3
92.4
#5/124
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Sonnet 5.5
Not ranked
MiniMax M3
Not ranked
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.7) differ from the provisional-lane categories. Unranked scores sit on the provisional lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Supported evidence per lane · bars run 0–100Methodology

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 Sonnet 5.5
$0.007
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 Sonnet 5.5
$0.13
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 Sonnet 5.5
$0.18
Fits in one request
MiniMax M3
$0.03
Fits in one request

MiniMax M3 has the lower modeled cost

Costs use the listed standard API rates.

Cached input falls back to the list input rate only where a cached rate is unpublished

Specification differences

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

Cached-input rate

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

Claude Sonnet 5.5

$0.2 per 1M cached input tokens

Claude API pricing

MiniMax M3

$0.06 per 1M cached input tokens

Reasoning profile

Claude Sonnet 5.5

Reasoning

MiniMax M3

Non-Reasoning

Weight access

Claude Sonnet 5.5

Proprietary

MiniMax M3

Open Weight

License

Claude Sonnet 5.5

Proprietary

MiniMax M3

Open Weight

Release date

Claude Sonnet 5.5

2026-09-28

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 Sonnet 5.5 has the higher public score, 80.49 versus 54.78, and the 90% score intervals do not overlap.
Workload cost
Repository review: $0.13 vs $0.0186. Cache-heavy agent loop: $0.18 vs $0.03.
Context tradeoff
Both models list 1M.
Run the same representative tasks against both endpoints before changing production traffic.

Questions

Which is better, Claude Sonnet 5.5 or MiniMax M3?

Claude Sonnet 5.5 has the higher public score, 80.49 versus 54.78, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.

Which is better for coding, Claude Sonnet 5.5 or MiniMax M3?

Claude Sonnet 5.5 scores higher for coding on the public lane, 79.6 to 38.7. Claude Sonnet 5.5 is scored on Estimated evidence for coding, so the reading is directional rather than like-for-like. BenchLM does not name a winner for coding from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which is better for agentic tasks, Claude Sonnet 5.5 or MiniMax M3?

Claude Sonnet 5.5 leads the public agentic tasks lane, 66.1 to 39.7, with Supported evidence for both models and non-overlapping 90% intervals.

Which costs less, Claude Sonnet 5.5 or MiniMax M3?

For the stated presets, chat costs $0.007 on Claude Sonnet 5.5 and $0.0009 on MiniMax M3; repository review costs $0.13 and $0.0186; the cache-heavy agent loop costs $0.18 and $0.03. Costs use the listed standard API rates.

Which has the larger context window, Claude Sonnet 5.5 or MiniMax M3?

Both models list the same context window, 1M.

Benchmark evidence

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

Browse raw public benchmark evidence72 rows

Agentic

  • Terminal-Bench 4.0

    Claude Sonnet 5.570.60%
    Source
    MiniMax M3—

    Not directly comparable

  • HLE w/ tools

    Claude Sonnet 5.564.5%
    Source
    MiniMax M3—

    Not directly comparable

  • DRACO

    Claude Sonnet 5.587.0%
    Source
    MiniMax M3—

    Not directly comparable

  • Terminal-Bench-Science 0.1

    Claude Sonnet 5.559.9%
    Source
    MiniMax M3—

    Not directly comparable

  • LAB all-pass (Harvey held-out)

    Claude Sonnet 5.510.0%
    Source
    MiniMax M3—

    Not directly comparable

  • LAB criterion-pass (Harvey held-out)

    Claude Sonnet 5.593.1%
    Source
    MiniMax M3—

    Not directly comparable

  • Toolathlon Verified Pass@3

    Claude Sonnet 5.585.2%
    Source
    MiniMax M3—

    Not directly comparable

  • Toolathlon Verified Pass³

    Claude Sonnet 5.568.5%
    Source
    MiniMax M3—

    Not directly comparable

  • Toolathlon Verified avg. turns

    Claude Sonnet 5.531.6 turns
    Source
    MiniMax M3—

    Not directly comparable

  • AutomationBench (Zapier 1.0.6)

    Claude Sonnet 5.544.7%
    Source
    MiniMax M3—

    Not directly comparable

  • Toolathlon-Verified

    Claude Sonnet 5.577.8%
    Source
    MiniMax M3—

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Sonnet 5.5—
    MiniMax M366.0%
    Source

    Not directly comparable

  • BrowseComp

    Claude Sonnet 5.5—
    MiniMax M383.5%
    Source

    Not directly comparable

  • OSWorld-Verified

    Claude Sonnet 5.5—
    MiniMax M370.1%
    Source

    Not directly comparable

  • MCP Atlas

    Claude Sonnet 5.5—
    MiniMax M374.2%
    Source

    Not directly comparable

  • Claw-Eval

    Claude Sonnet 5.5—
    MiniMax M374.5%
    Source

    Not directly comparable

  • BankerToolBench

    Claude Sonnet 5.5—
    MiniMax M376.1%
    Source

    Not directly comparable

  • ResearchClawBench

    Claude Sonnet 5.5—
    MiniMax M319.8%
    Source

    Not directly comparable

  • OSWorld 2.0

    Claude Sonnet 5.5—
    MiniMax M34.6%
    Source

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Sonnet 5.5—
    MiniMax M353.6%
    Source

    Not directly comparable

Coding

  • FrontierCode 1.1 Main

    Claude Sonnet 5.546.2%
    Source
    MiniMax M3—

    Not directly comparable

  • cursorBench40

    Claude Sonnet 5.555.5%
    Source
    MiniMax M3—

    Not directly comparable

  • SWE-bench Pro

    Claude Sonnet 5.581.3%
    Source
    MiniMax M359%
    Source

    Claude Sonnet 5.5 leads this result

  • SWE Multilingual

    Claude Sonnet 5.590.3%
    Source
    MiniMax M3—

    Not directly comparable

  • SWE Multimodal

    Claude Sonnet 5.554.3%
    Source
    MiniMax M3—

    Not directly comparable

  • DeepSWE

    Claude Sonnet 5.571.0%
    Source
    MiniMax M3—

    Not directly comparable

  • FrontierCode 1.1 Extended

    Claude Sonnet 5.559.1%
    Source
    MiniMax M3—

    Not directly comparable

  • ProgramBench

    Claude Sonnet 5.579.7%
    Source
    MiniMax M3—

    Not directly comparable

  • FrontierSWE v2

    Claude Sonnet 5.561.9%
    Source
    MiniMax M3—

    Not directly comparable

  • SWE-bench Verified

    Claude Sonnet 5.5—
    MiniMax M380.5%
    Source

    Not directly comparable

  • Terminal-Bench 2.1

    Claude Sonnet 5.5—
    MiniMax M366.0%
    Source

    Not directly comparable

  • NL2Repo

    Claude Sonnet 5.5—
    MiniMax M342.1%
    Source

    Not directly comparable

  • VIBE V2

    Claude Sonnet 5.5—
    MiniMax M350.1%
    Source

    Not directly comparable

  • SVG-Bench

    Claude Sonnet 5.5—
    MiniMax M363.7%
    Source

    Not directly comparable

  • KernelBench Hard

    Claude Sonnet 5.5—
    MiniMax M328.8%
    Source

    Not directly comparable

  • OpenHarmony Bench

    Claude Sonnet 5.5—
    MiniMax M348.4%
    Source

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Sonnet 5.5—
    MiniMax M382.2%
    Source

    Not directly comparable

  • SWE-bench (Vals)

    Claude Sonnet 5.5—
    MiniMax M375.0%
    Source

    Not directly comparable

Multimodal

  • Chartography (no tools)

    Claude Sonnet 5.561.6%
    Source
    MiniMax M3—

    Not directly comparable

  • Chartography (tools)

    Claude Sonnet 5.590.2%
    Source
    MiniMax M3—

    Not directly comparable

  • BenchCAD Vision2Code (no tools)

    Claude Sonnet 5.50.747
    Source
    MiniMax M3—

    Not directly comparable

  • BenchCAD Vision2Code (tools)

    Claude Sonnet 5.50.963
    Source
    MiniMax M3—

    Not directly comparable

  • Biomedical image analysis

    Claude Sonnet 5.572.2%
    Source
    MiniMax M3—

    Not directly comparable

  • OfficeQA

    Claude Sonnet 5.576.9%
    Source
    MiniMax M3—

    Not directly comparable

  • OfficeQA Pro

    Claude Sonnet 5.565.6%
    Source
    MiniMax M345.1%
    Source

    Claude Sonnet 5.5 leads this result

  • OmniDocBench 1.5

    Claude Sonnet 5.5—
    MiniMax M391.6%
    Source

    Not directly comparable

  • MMMU-Pro

    Claude Sonnet 5.5—
    MiniMax M378.1%
    Source

    Not directly comparable

  • VideoMMMU

    Claude Sonnet 5.5—
    MiniMax M384.6%
    Source

    Not directly comparable

  • Video-MME (with subtitle)

    Claude Sonnet 5.5—
    MiniMax M385.4%
    Source

    Not directly comparable

Knowledge

  • HealthBench (raw)

    Claude Sonnet 5.569.4%
    Source
    MiniMax M3—

    Not directly comparable

  • HealthBench (length-adjusted)

    Claude Sonnet 5.565.4%
    Source
    MiniMax M3—

    Not directly comparable

  • HealthBench Professional (raw)

    Claude Sonnet 5.577.1%
    Source
    MiniMax M3—

    Not directly comparable

  • HealthBench Professional

    Claude Sonnet 5.569.2%
    Source
    MiniMax M3—

    Not directly comparable

  • BioMysteryBench (human-solvable)

    Claude Sonnet 5.589.2%
    Source
    MiniMax M3—

    Not directly comparable

  • BioMysteryBench (human-difficult)

    Claude Sonnet 5.544.7%
    Source
    MiniMax M3—

    Not directly comparable

  • SpatialBench Verified

    Claude Sonnet 5.572.5%
    Source
    MiniMax M3—

    Not directly comparable

  • SingleCellBench

    Claude Sonnet 5.559.1%
    Source
    MiniMax M3—

    Not directly comparable

  • Protein Design

    Claude Sonnet 5.551.0%
    Source
    MiniMax M3—

    Not directly comparable

  • Morphology-to-molecule matching

    Claude Sonnet 5.525.0%
    Source
    MiniMax M3—

    Not directly comparable

  • Medicinal chemistry

    Claude Sonnet 5.565.3%
    Source
    MiniMax M3—

    Not directly comparable

  • Protein Design library ranking

    Claude Sonnet 5.554.8%
    Source
    MiniMax M3—

    Not directly comparable

  • De novo protein-binder design

    Claude Sonnet 5.582.3%
    Source
    MiniMax M3—

    Not directly comparable

  • Protocols (troubleshooting)

    Claude Sonnet 5.567.3%
    Source
    MiniMax M3—

    Not directly comparable

  • Protocols (understanding)

    Claude Sonnet 5.566.6%
    Source
    MiniMax M3—

    Not directly comparable

  • HLE w/o tools

    Claude Sonnet 5.556.9%
    Source
    MiniMax M3—

    Not directly comparable

  • GPQA Diamond (Vals)

    Claude Sonnet 5.5—
    MiniMax M392.7%
    Source

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Sonnet 5.5—
    MiniMax M384.2%
    Source

    Not directly comparable

Multilingual

  • GMMLU

    Claude Sonnet 5.592.1%
    Source
    MiniMax M3—

    Not directly comparable

  • MILU

    Claude Sonnet 5.591.6%
    Source
    MiniMax M3—

    Not directly comparable

Math

  • ArXivMath Aug. 2026 (no tools)

    Claude Sonnet 5.586.8%
    Source
    MiniMax M3—

    Not directly comparable

  • ArXivMath Aug. 2026 (tools)

    Claude Sonnet 5.595.2%
    Source
    MiniMax M3—

    Not directly comparable

  • USAMO 2026

    Claude Sonnet 5.5—
    MiniMax M385.7%
    Source

    Not directly comparable

72 public results · 2 shared

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Last updated September 28, 2026