MiniMax M3 vs Qwen3.7 Plus

Updated November 13, 2026. Rank says Qwen3.7 Plus is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

Decision reading

Qwen3.7 Plus has the higher public point estimate, 53.66 versus 49.41. Their conditional score ranges overlap. These ranges do not establish rank confidence. 12 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

MiniMax M3

MiniMax

49.41/100

Supported · Public rank #94

90% interval 34.3–64.5

Model B

Qwen3.7 Plus

Alibaba

53.66/100

Estimated · Public rank #75

Conditional range 43.9–63.4

API price per 1M tokens

MiniMax M3: $0.30 input / $1.20 output

Qwen3.7 Plus: No comparable API price

Context window

MiniMax M3: 1M

Qwen3.7 Plus: 1M

Released

MiniMax M3: June 1, 2026

Qwen3.7 Plus: June 3, 2026

Shared results: 12
MiniMax M3 only: 16
Qwen3.7 Plus only: 41
Like-for-like categories: 1 / 8

Supported: MiniMax M3 · Estimated: Qwen3.7 Plus. Conditional ranges do not establish rank confidence.How 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
MiniMax M3
MiniMax M3 has the higher public agentic point estimate, 38.5 to 34.8, with Supported evidence for both models. The conditional ranges do not establish rank confidence.
Confidence: limited

Show secondary and unsupported calls

Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Qwen3.7 Plus 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
Chat turn cost
1K fresh input + 500 output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates
Repository review cost
50K fresh input + 3K output tokens
Not enough matched evidence
A complete comparable API-rate estimate is not available for both models.
Confidence: listed-rates

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.

Pick the job you would use them for

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

37.9MiniMax M340.1Qwen3.7 Plus

Directional only · BenchAlign v5.8

Qwen3.7 Plus has the higher coding point estimate. Conditional score ranges do not establish rank confidence.

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

Open the coding leaderboard Shortlist models for this job

Same basis rules as the category table below

Or describe your own job

The LLM Selector reads what you need a model for and returns a shortlist, ranked in the same order the job pages publish.

What do you need a model for?

Describe the task and constraints. This selector recommends models; it cannot carry out the task or access your files and accounts.

We keep what you type here, drafts included, for 180 days, and after that only the job and requirements read from it. Nothing is tied to your IP address or account. Leave out names and other personal details. Privacy

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.

OSWorld-VerifiedAgentic
Normalized gap 3.2
MiniMax M3:70.1%
Qwen3.7 Plus:73.3%
MiniMax M3 source Qwen3.7 Plus source
SWE-bench VerifiedCoding
Normalized gap 2.8
MiniMax M3:80.5%
Qwen3.7 Plus:77.7%
MiniMax M3 source Qwen3.7 Plus source
OSWorld 2.0Agentic
Normalized gap 1.8
MiniMax M3:4.6%
Qwen3.7 Plus:2.8%
Shared source
SWE-bench ProCoding
Normalized gap 1.4
MiniMax M3:59%
Qwen3.7 Plus:57.6%
MiniMax M3 source Qwen3.7 Plus source
MMMU-ProMultimodal
Normalized gap 0.9
MiniMax M3:78.1%
Qwen3.7 Plus:79%
MiniMax M3 source Qwen3.7 Plus source

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 v5.8 lane for agentic, coding, reasoning, multimodal, 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

MiniMax M3: 38.5; Supported · #75/135
Qwen3.7 Plus: 34.8; Supported · #84/135
Basis: BenchAlign v5.8 lane · 10 vs 11 public rows
Reading: MiniMax M3 leads · intervals overlap

Coding

Directional only

MiniMax M3: 37.9; Supported · #74/162
Qwen3.7 Plus: 40.1; Estimated · #71/162
Basis: BenchAlign v5.8 lane · 10 vs 7 public rows
Reading: Directional only

Reasoning

Directional only

MiniMax M3: 38.7; Estimated · #89/160
Qwen3.7 Plus: 46.3; Estimated · #62/160
Basis: BenchAlign v5.8 lane · 0 vs 2 public rows
Reading: Directional only

Multimodal

Directional only

MiniMax M3: 53.7; Estimated · #49/67
Qwen3.7 Plus: 56.1; Estimated · #45/67
Basis: BenchAlign v5.8 lane · 5 vs 15 public rows
Reading: Directional only

Knowledge

Directional only

MiniMax M3: 54.9; Supported · #61/180
Qwen3.7 Plus: 53.4; Estimated · #74/180
Basis: BenchAlign v5.8 lane · 2 vs 7 public rows
Reading: Directional only

Instruction following

Directional only

MiniMax M3: 93.8; #6/157
Qwen3.7 Plus: 92.8; #18/157
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Directional only

Multilingual

Not comparable

MiniMax M3: Not ranked
Qwen3.7 Plus: 95.7; #3/17
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

MiniMax M3: Not ranked
Qwen3.7 Plus: 60.1; Unranked · 4 rankable rows
Basis: Provisional lane · 1 vs 2 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for MiniMax M3 and Qwen3.7 Plus
Category	MiniMax M3	Qwen3.7 Plus	Basis	Reading
Agentic	38.5Supported · #75/135	34.8Supported · #84/135	Like-for-likeBenchAlign v5.8 lane · 10 vs 11 public rows	MiniMax M3 leads · intervals overlap
Coding	37.9Supported · #74/162	40.1Estimated · #71/162	Directional onlyBenchAlign v5.8 lane · 10 vs 7 public rows	Directional only
Reasoning	38.7Estimated · #89/160	46.3Estimated · #62/160	Directional onlyBenchAlign v5.8 lane · 0 vs 2 public rows	Directional only
Multimodal	53.7Estimated · #49/67	56.1Estimated · #45/67	Directional onlyBenchAlign v5.8 lane · 5 vs 15 public rows	Directional only
Knowledge	54.9Supported · #61/180	53.4Estimated · #74/180	Directional onlyBenchAlign v5.8 lane · 2 vs 7 public rows	Directional only
Instruction following	93.8#6/157	92.8#18/157	Directional onlyProvisional lane · 0 vs 1 weighted rows	Directional only
Multilingual	Not ranked	95.7#3/17	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	60.1Unranked · 4 rankable rows	Not comparableProvisional lane · 1 vs 2 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, reasoning, multimodal, and knowledge denominators (BenchAlign v5.8) 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

MiniMax M3: $0.0009; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

Qwen3.7 Plus has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

MiniMax M3: $0.0186; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

Qwen3.7 Plus has no comparable published API token rate.

Cache-heavy agent loop

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

MiniMax M3: $0.03; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request; Cached-input rate unavailable

Qwen3.7 Plus has no comparable published API token rate.

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

Price against score, among all priced models

Overall score against output price per 1M tokens, one model per family. Pricing as of November 12, 2026.

MiniMax M3

6 models score at least as high as MiniMax M3 for the same price or less. The nearest is DeepSeek V4.1 Flash 1017 (score 64.5, also $1.20 per 1M output tokens).
Qwen3.7 Plus has no public API price, so it is not plotted.

Gray dots are the other priced models. The dark step line is the efficiency frontier: for a model under it, another model costs no more and scores at least as high.

See MiniMax M3 on the full price vs performance chart

Specification differences

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

SpecificationMiniMax M3Qwen3.7 Plus

Context window

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

MiniMax M3

Qwen3.7 Plus

API model ID

MiniMax M3

Not sourced

Qwen3.7 Plus

Not sourced

Cached-input rate

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

MiniMax M3

$0.06 per 1M cached input tokens

Qwen3.7 Plus

No comparable hosted API rate

Documented inputs

MiniMax M3

text, image, video

MiniMax-M3 model card

Qwen3.7 Plus

text, image, video

Qwen Cloud model page for qwen3.7-plus

Documented outputs

MiniMax M3

text

MiniMax-M3 model card

Qwen3.7 Plus

text

Qwen Cloud model page for qwen3.7-plus

Provider availability

MiniMax M3

Not sourced

Qwen3.7 Plus

Not sourced

Reasoning profile

MiniMax M3

Non-Reasoning

Qwen3.7 Plus

Reasoning

Weight access

MiniMax M3

Open Weight

Qwen3.7 Plus

Proprietary

License

MiniMax M3

Open Weight

Qwen3.7 Plus

Proprietary

Release date

MiniMax M3

2026-06-01

Qwen3.7 Plus

2026-06-03

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: Qwen3.7 Plus has the higher public point estimate, 53.66 versus 49.41. Their conditional score ranges overlap. These ranges do not establish rank confidence.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Both models list 1M.

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

Questions

Which is better, MiniMax M3 or Qwen3.7 Plus?

Qwen3.7 Plus has the higher public point estimate, 53.66 versus 49.41. Their conditional score ranges overlap. These ranges do not establish rank confidence. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, MiniMax M3 or Qwen3.7 Plus?

Qwen3.7 Plus scores higher for coding on the public lane, 40.1 to 37.9. Qwen3.7 Plus 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, MiniMax M3 or Qwen3.7 Plus?

MiniMax M3 has the higher public agentic tasks point estimate, 38.5 to 34.8, with Supported evidence for both models. The conditional ranges do not establish rank confidence.

Which costs less, MiniMax M3 or Qwen3.7 Plus?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, MiniMax M3 or Qwen3.7 Plus?

Both models list the same context window, 1M.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

MiniMax M3

API / mo$1,125

Self-host / mo$13,981

Break-evenNot reached at 70% load

Qwen3.7 Plus

API / moNo API price on file

Self-host / moNot listed

Break-even—

Proprietary model — self-hosting not applicable.

Model the full break-even

Benchmark evidence

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

Browse raw public benchmark evidence69 rows

Agentic

Terminal-Bench 2.1
MiniMax M366.0%
Source
Qwen3.7 Plus—
Not directly comparable
BrowseComp
MiniMax M383.5%
Source
Qwen3.7 Plus—
Not directly comparable
OSWorld-Verified
MiniMax M370.1%
Source
Qwen3.7 Plus73.3%
Source
Qwen3.7 Plus leads this result
MCP Atlas
MiniMax M374.2%
Source
Qwen3.7 Plus73.2%
Source
MiniMax M3 leads this result
Claw-Eval
MiniMax M374.5%
Source
Qwen3.7 Plus62.7%
Source
MiniMax M3 leads this result
BankerToolBench
MiniMax M376.1%
Source
Qwen3.7 Plus—
Not directly comparable
ResearchClawBench
MiniMax M319.8%
Source
Qwen3.7 Plus—
Not directly comparable
OSWorld 2.0
Shared source
MiniMax M34.6%
Qwen3.7 Plus2.8%
MiniMax M3 leads this result
Terminal-Bench 2.1 (Vals)
MiniMax M353.6%
Source
Qwen3.7 Plus52.8%
Source
MiniMax M3 leads this result
MazeBench
MiniMax M30%
Source
Qwen3.7 Plus—
Not directly comparable
Terminal-Bench 2.0
MiniMax M3—
Qwen3.7 Plus70.3%
Source
Not directly comparable
QwenClawBench
MiniMax M3—
Qwen3.7 Plus61.8%
Source
Not directly comparable
BFCL v4
MiniMax M3—
Qwen3.7 Plus72.9%
Source
Not directly comparable
VITA-Bench
MiniMax M3—
Qwen3.7 Plus45.6%
Source
Not directly comparable
DeepPlanning
MiniMax M3—
Qwen3.7 Plus62.3%
Source
Not directly comparable
AndroidWorld
MiniMax M3—
Qwen3.7 Plus81.0%
Source
Not directly comparable

Coding

SWE-bench Verified
MiniMax M380.5%
Source
Qwen3.7 Plus77.7%
Source
MiniMax M3 leads this result
SWE-bench Pro
MiniMax M359%
Source
Qwen3.7 Plus57.6%
Source
MiniMax M3 leads this result
Terminal-Bench 2.1
MiniMax M366.0%
Source
Qwen3.7 Plus—
Not directly comparable
NL2Repo
MiniMax M342.1%
Source
Qwen3.7 Plus41.1%
Source
MiniMax M3 leads this result
VIBE V2
MiniMax M350.1%
Source
Qwen3.7 Plus—
Not directly comparable
SVG-Bench
MiniMax M363.7%
Source
Qwen3.7 Plus—
Not directly comparable
KernelBench Hard
MiniMax M328.8%
Source
Qwen3.7 Plus—
Not directly comparable
OpenHarmony Bench v1.0
MiniMax M348.4%
Source
Qwen3.7 Plus—
Not directly comparable
LiveCodeBench (Vals)
MiniMax M382.2%
Source
Qwen3.7 Plus—
Not directly comparable
SWE-bench (Vals)
MiniMax M375.0%
Source
Qwen3.7 Plus—
Not directly comparable
Terminal-Bench 2.0
MiniMax M3—
Qwen3.7 Plus70.3%
Source
Not directly comparable
SWE Multilingual
MiniMax M3—
Qwen3.7 Plus75.8%
Source
Not directly comparable
SciCode
MiniMax M3—
Qwen3.7 Plus51.3%
Source
Not directly comparable
LiveCodeBench v6
MiniMax M3—
Qwen3.7 Plus89.6%
Source
Not directly comparable

Reasoning

CritPt
MiniMax M3—
Qwen3.7 Plus9.1%
Source
Not directly comparable
MRCRv2
MiniMax M3—
Qwen3.7 Plus91.7%
Source
Not directly comparable

Multimodal

OfficeQA Pro
MiniMax M345.1%
Source
Qwen3.7 Plus—
Not directly comparable
OmniDocBench 1.5
MiniMax M391.6%
Source
Qwen3.7 Plus91.4%
Source
MiniMax M3 leads this result
MMMU-Pro
MiniMax M378.1%
Source
Qwen3.7 Plus79%
Source
Qwen3.7 Plus leads this result
VideoMMMU
MiniMax M384.6%
Source
Qwen3.7 Plus85.4%
Source
Qwen3.7 Plus leads this result
Video-MME (with subtitle)
MiniMax M385.4%
Source
Qwen3.7 Plus88.0%
Source
Qwen3.7 Plus leads this result
MathVision
MiniMax M3—
Qwen3.7 Plus90.3%
Source
Not directly comparable
CharXiv
MiniMax M3—
Qwen3.7 Plus85.9%
Source
Not directly comparable
ERQA
MiniMax M3—
Qwen3.7 Plus69.8%
Source
Not directly comparable
MedXpertQA (MM)
MiniMax M3—
Qwen3.7 Plus71.0%
Source
Not directly comparable
ScreenSpot Pro
MiniMax M3—
Qwen3.7 Plus79.0%
Source
Not directly comparable
SimpleVQA
MiniMax M3—
Qwen3.7 Plus81.7%
Source
Not directly comparable
MMSearch-Plus
MiniMax M3—
Qwen3.7 Plus41.4%
Source
Not directly comparable
RealWorldQA
MiniMax M3—
Qwen3.7 Plus86.9%
Source
Not directly comparable
OCRBench V2
MiniMax M3—
Qwen3.7 Plus70.7%
Source
Not directly comparable
ODINW13
MiniMax M3—
Qwen3.7 Plus51.1%
Source
Not directly comparable
MLVU (M-Avg)
MiniMax M3—
Qwen3.7 Plus87.4%
Source
Not directly comparable

Knowledge

GPQA Diamond (Vals)
MiniMax M392.7%
Source
Qwen3.7 Plus—
Not directly comparable
MMLU-Pro (Vals)
MiniMax M384.2%
Source
Qwen3.7 Plus—
Not directly comparable
GPQA
MiniMax M3—
Qwen3.7 Plus90.3%
Source
Not directly comparable
GPQA-D
MiniMax M3—
Qwen3.7 Plus90.3%
Source
Not directly comparable
HLE
MiniMax M3—
Qwen3.7 Plus34.7%
Source
Not directly comparable
MMLU-Pro
MiniMax M3—
Qwen3.7 Plus88.5%
Source
Not directly comparable
MMLU-Redux
MiniMax M3—
Qwen3.7 Plus94.5%
Source
Not directly comparable
SuperGPQA
MiniMax M3—
Qwen3.7 Plus71.4%
Source
Not directly comparable
MMMLU
MiniMax M3—
Qwen3.7 Plus89.0%
Source
Not directly comparable

Multilingual

MMLU-ProX
MiniMax M3—
Qwen3.7 Plus85.4%
Source
Not directly comparable
NOVA-63
MiniMax M3—
Qwen3.7 Plus58.8%
Source
Not directly comparable
INCLUDE
MiniMax M3—
Qwen3.7 Plus83.0%
Source
Not directly comparable
MAXIFE
MiniMax M3—
Qwen3.7 Plus88.8%
Source
Not directly comparable
PolyMath
MiniMax M3—
Qwen3.7 Plus84.0%
Source
Not directly comparable

Instruction following

IFEval
MiniMax M3—
Qwen3.7 Plus94.6%
Source
Not directly comparable
IFBench
MiniMax M3—
Qwen3.7 Plus79.1%
Source
Not directly comparable

Math

USAMO 2026
MiniMax M385.7%
Source
Qwen3.7 Plus—
Not directly comparable
HMMT Feb 2026
MiniMax M3—
Qwen3.7 Plus92.9%
Source
Not directly comparable
IMOAnswerBench
MiniMax M3—
Qwen3.7 Plus86.0%
Source
Not directly comparable
Apex
MiniMax M3—
Qwen3.7 Plus22.7%
Source
Not directly comparable
FrontierMath v2 (Tiers 1-3)
MiniMax M3—
Qwen3.7 Plus34.386%
Source
Not directly comparable

69 public results · 12 shared

Related comparisons

Compare API pricing Read the methodology Open the model selector

Watch MiniMax M3 vs Qwen3.7 Plus

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 7,000+ subscribers.

Last updated November 13, 2026

MiniMax M3 vs Qwen3.7 Plus

Decision reading

Which one for your work

Agentic work

Coding work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

Or describe your own job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Agentic

Coding

Reasoning

Multimodal

Knowledge

Instruction following

Multilingual

Math

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Price against score, among all priced models

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

If you already use one of these models

Questions

Which is better, MiniMax M3 or Qwen3.7 Plus?

Which is better for coding, MiniMax M3 or Qwen3.7 Plus?

Which is better for agentic tasks, MiniMax M3 or Qwen3.7 Plus?

Which costs less, MiniMax M3 or Qwen3.7 Plus?

Which has the larger context window, MiniMax M3 or Qwen3.7 Plus?

Self-host vs API cost

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

Related comparisons

Watch MiniMax M3 vs Qwen3.7 Plus