GPT-4.1 mini vs Qwen3.7 Plus

Decision reading

Qwen3.7 Plus has the higher public score, 55.76 versus 28.68, and the 90% score intervals do not overlap.

3 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

GPT-4.1 mini

OpenAI

28.68/100

Estimated · Public rank #167

90% interval 22.1–35.3

Model B

Qwen3.7 Plus

Alibaba

55.76/100

Supported · Public rank #53

90% interval 45.6–65.9

Updated September 22, 2026. Rank says Qwen3.7 Plus is ahead. Price, access, and your workload can each overturn that. Public scores include evidence status and uncertainty.

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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.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls

Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
GPT-4.1 mini and Qwen3.7 Plus are scored on Estimated evidence for coding, so the reading is directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
GPT-4.1 mini is not ranked on the public lane for agentic, so no winner is named for agentic.
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: rate-fallback
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.

24.9GPT-4.1 mini44.3Qwen3.7 Plus

Directional only · BenchAlign v5.6

Qwen3.7 Plus 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 leaderboard Shortlist models for this job

What is actually comparable

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

2 GPT-4.1 mini only

3 Shared

49 Qwen3.7 Plus only

Shared results: 3
GPT-4.1 mini only: 2
Qwen3.7 Plus only: 49
Like-for-like categories: 0 / 8

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

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign v5.6 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.

Coding

Directional only

GPT-4.1 mini: 24.9; Estimated · #111/135
Qwen3.7 Plus: 44.3; Estimated · #51/135
Basis: BenchAlign v5.6 lane · 1 vs 7 public rows
Reading: Directional only

Knowledge

Directional only

GPT-4.1 mini: 29.8; Supported · #128/160
Qwen3.7 Plus: 50.4; Estimated · #53/160
Basis: BenchAlign v5.6 lane · 2 vs 7 public rows
Reading: Directional only

Instruction following

Directional only

GPT-4.1 mini: 42.8; #94/124
Qwen3.7 Plus: 89.2; #18/124
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Directional only

Agentic

Not comparable

GPT-4.1 mini: Not ranked
Qwen3.7 Plus: 35.1; Supported · #55/104
Basis: BenchAlign v5.6 lane · 0 vs 11 public rows
Reading: Not comparable

Reasoning

Not comparable

GPT-4.1 mini: 51.3; Unranked · 2 rankable rows
Qwen3.7 Plus: 74.0; Unranked · 3 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

GPT-4.1 mini: 46.6; Unranked · 1 rankable row
Qwen3.7 Plus: 72.4; #19/50
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Multilingual

Not comparable

GPT-4.1 mini: Not ranked
Qwen3.7 Plus: 78.9; #3/12
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

GPT-4.1 mini: 28.4; Unranked · 1 rankable row
Qwen3.7 Plus: 78.2; Unranked · 3 rankable rows
Basis: Provisional lane · 1 vs 1 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for GPT-4.1 mini and Qwen3.7 Plus
Category	GPT-4.1 mini	Qwen3.7 Plus	Basis	Reading
Coding	24.9Estimated · #111/135	44.3Estimated · #51/135	Directional onlyBenchAlign v5.6 lane · 1 vs 7 public rows	Directional only
Knowledge	29.8Supported · #128/160	50.4Estimated · #53/160	Directional onlyBenchAlign v5.6 lane · 2 vs 7 public rows	Directional only
Instruction following	42.8#94/124	89.2#18/124	Directional onlyProvisional lane · 0 vs 1 weighted rows	Directional only
Agentic	Not ranked	35.1Supported · #55/104	Not comparableBenchAlign v5.6 lane · 0 vs 11 public rows	Not comparable
Reasoning	51.3Unranked · 2 rankable rows	74.0Unranked · 3 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multimodal	46.6Unranked · 1 rankable row	72.4#19/50	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Multilingual	Not ranked	78.9#3/12	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	28.4Unranked · 1 rankable row	78.2Unranked · 3 rankable rows	Not comparableProvisional lane · 1 vs 1 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign v5.6) 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.

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.

SWE-bench Verified
Coding
GPT-4.1 mini: 23.6%Qwen3.7 Plus: 77.7%Normalized gap 54.1GPT-4.1 mini source Qwen3.7 Plus source
GPQA
Knowledge
GPT-4.1 mini: 64.2%Qwen3.7 Plus: 90.3%Normalized gap 26.1GPT-4.1 mini source Qwen3.7 Plus source

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

GPT-4.1 mini: $0.0012; 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

GPT-4.1 mini: $0.0248; 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

GPT-4.1 mini: $0.104; Fits in one request; Cached input priced at the published list-input rate
Qwen3.7 Plus: API rate not published; Fits in one request; Cached-input rate unavailable

GPT-4.1 mini has no published cached-input rate, so cached tokens use its listed input rate. Qwen3.7 Plus has no comparable published API token rate.

Specification differences

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

SpecificationGPT-4.1 miniQwen3.7 Plus

Context window

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

GPT-4.1 mini

Qwen3.7 Plus

API model ID

GPT-4.1 mini

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.

GPT-4.1 mini

Not published

Qwen3.7 Plus

No comparable hosted API rate

Documented inputs

GPT-4.1 mini

Not sourced

Qwen3.7 Plus

Not sourced

Documented outputs

GPT-4.1 mini

Not sourced

Qwen3.7 Plus

Not sourced

Provider availability

GPT-4.1 mini

Not sourced

Qwen3.7 Plus

Not sourced

Reasoning profile

GPT-4.1 mini

Non-Reasoning

Qwen3.7 Plus

Reasoning

Weight access

GPT-4.1 mini

Proprietary

Qwen3.7 Plus

Proprietary

License

GPT-4.1 mini

Proprietary

Qwen3.7 Plus

Proprietary

Release date

GPT-4.1 mini

2025-04-14

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 score, 55.76 versus 28.68, and the 90% score intervals do not overlap.
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.

Benchmark evidence

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

Browse raw public benchmark evidence54 rows

Agentic

Terminal-Bench 2.0
GPT-4.1 mini—
Qwen3.7 Plus70.3%
Source
Not directly comparable
QwenClawBench
GPT-4.1 mini—
Qwen3.7 Plus61.8%
Source
Not directly comparable
Claw-Eval
GPT-4.1 mini—
Qwen3.7 Plus62.7%
Source
Not directly comparable
BFCL v4
GPT-4.1 mini—
Qwen3.7 Plus72.9%
Source
Not directly comparable
MCP Atlas
GPT-4.1 mini—
Qwen3.7 Plus73.2%
Source
Not directly comparable
VITA-Bench
GPT-4.1 mini—
Qwen3.7 Plus45.6%
Source
Not directly comparable
DeepPlanning
GPT-4.1 mini—
Qwen3.7 Plus62.3%
Source
Not directly comparable
OSWorld-Verified
GPT-4.1 mini—
Qwen3.7 Plus73.3%
Source
Not directly comparable
AndroidWorld
GPT-4.1 mini—
Qwen3.7 Plus81.0%
Source
Not directly comparable
OSWorld 2.0
GPT-4.1 mini—
Qwen3.7 Plus2.8%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
GPT-4.1 mini—
Qwen3.7 Plus52.8%
Source
Not directly comparable

Coding

SWE-bench Verified
GPT-4.1 mini23.6%
Source
Qwen3.7 Plus77.7%
Source
Qwen3.7 Plus leads this result
Terminal-Bench 2.0
GPT-4.1 mini—
Qwen3.7 Plus70.3%
Source
Not directly comparable
SWE-bench Pro
GPT-4.1 mini—
Qwen3.7 Plus57.6%
Source
Not directly comparable
SWE Multilingual
GPT-4.1 mini—
Qwen3.7 Plus75.8%
Source
Not directly comparable
NL2Repo
GPT-4.1 mini—
Qwen3.7 Plus41.1%
Source
Not directly comparable
SciCode
GPT-4.1 mini—
Qwen3.7 Plus51.3%
Source
Not directly comparable
LiveCodeBench
GPT-4.1 mini—
Qwen3.7 Plus89.6%
Source
Not directly comparable

Reasoning

CritPt
GPT-4.1 mini—
Qwen3.7 Plus9.1%
Source
Not directly comparable
MRCRv2
GPT-4.1 mini—
Qwen3.7 Plus91.7%
Source
Not directly comparable

Multimodal

MMMU-Pro
GPT-4.1 mini—
Qwen3.7 Plus79%
Source
Not directly comparable
MathVision
GPT-4.1 mini—
Qwen3.7 Plus90.3%
Source
Not directly comparable
CharXiv
GPT-4.1 mini—
Qwen3.7 Plus85.9%
Source
Not directly comparable
ERQA
GPT-4.1 mini—
Qwen3.7 Plus69.8%
Source
Not directly comparable
MedXpertQA (MM)
GPT-4.1 mini—
Qwen3.7 Plus71.0%
Source
Not directly comparable
ScreenSpot Pro
GPT-4.1 mini—
Qwen3.7 Plus79.0%
Source
Not directly comparable
SimpleVQA
GPT-4.1 mini—
Qwen3.7 Plus81.7%
Source
Not directly comparable
MMSearch-Plus
GPT-4.1 mini—
Qwen3.7 Plus41.4%
Source
Not directly comparable
RealWorldQA
GPT-4.1 mini—
Qwen3.7 Plus86.9%
Source
Not directly comparable
OmniDocBench 1.5
GPT-4.1 mini—
Qwen3.7 Plus91.4%
Source
Not directly comparable
OCRBench V2
GPT-4.1 mini—
Qwen3.7 Plus70.7%
Source
Not directly comparable
ODINW13
GPT-4.1 mini—
Qwen3.7 Plus51.1%
Source
Not directly comparable
Video-MME (with subtitle)
GPT-4.1 mini—
Qwen3.7 Plus88.0%
Source
Not directly comparable
VideoMMMU
GPT-4.1 mini—
Qwen3.7 Plus85.4%
Source
Not directly comparable
MLVU (M-Avg)
GPT-4.1 mini—
Qwen3.7 Plus87.4%
Source
Not directly comparable

Knowledge

MMLU
GPT-4.1 mini87.5%
Source
Qwen3.7 Plus—
Not directly comparable
GPQA
GPT-4.1 mini64.2%
Source
Qwen3.7 Plus90.3%
Source
Qwen3.7 Plus leads this result
GPQA-D
GPT-4.1 mini—
Qwen3.7 Plus90.3%
Source
Not directly comparable
HLE
GPT-4.1 mini—
Qwen3.7 Plus34.7%
Source
Not directly comparable
MMLU-Pro
GPT-4.1 mini—
Qwen3.7 Plus88.5%
Source
Not directly comparable
MMLU-Redux
GPT-4.1 mini—
Qwen3.7 Plus94.5%
Source
Not directly comparable
SuperGPQA
GPT-4.1 mini—
Qwen3.7 Plus71.4%
Source
Not directly comparable
MMMLU
GPT-4.1 mini—
Qwen3.7 Plus89.0%
Source
Not directly comparable

Multilingual

MMLU-ProX
GPT-4.1 mini—
Qwen3.7 Plus85.4%
Source
Not directly comparable
NOVA-63
GPT-4.1 mini—
Qwen3.7 Plus58.8%
Source
Not directly comparable
INCLUDE
GPT-4.1 mini—
Qwen3.7 Plus83.0%
Source
Not directly comparable
MAXIFE
GPT-4.1 mini—
Qwen3.7 Plus88.8%
Source
Not directly comparable
PolyMath
GPT-4.1 mini—
Qwen3.7 Plus84.0%
Source
Not directly comparable

Instruction following

IFEval
GPT-4.1 mini88.5%
Source
Qwen3.7 Plus94.6%
Source
Qwen3.7 Plus leads this result
IFBench
GPT-4.1 mini—
Qwen3.7 Plus79.1%
Source
Not directly comparable

Math

FrontierMath v2 (Tiers 1-3)
GPT-4.1 mini4.483%
Source
Qwen3.7 Plus—
Not directly comparable
HMMT Feb 2026
GPT-4.1 mini—
Qwen3.7 Plus92.9%
Source
Not directly comparable
IMOAnswerBench
GPT-4.1 mini—
Qwen3.7 Plus86.0%
Source
Not directly comparable
Apex
GPT-4.1 mini—
Qwen3.7 Plus22.7%
Source
Not directly comparable

Questions

Which is better, GPT-4.1 mini or Qwen3.7 Plus?

Qwen3.7 Plus has the higher public score, 55.76 versus 28.68, 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, GPT-4.1 mini or Qwen3.7 Plus?

Qwen3.7 Plus scores higher for coding on the public lane, 44.3 to 24.9. GPT-4.1 mini and Qwen3.7 Plus are 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, GPT-4.1 mini or Qwen3.7 Plus?

GPT-4.1 mini is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, GPT-4.1 mini 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, GPT-4.1 mini or Qwen3.7 Plus?

Both models list the same context window, 1M.

Related comparisons

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Last updated September 22, 2026

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GPT-4.1 mini vs Qwen3.7 Plus

Which one for your work

Coding work

Agentic work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Category results, on a stated basis

Coding

Knowledge

Instruction following

Agentic

Reasoning

Multimodal

Multilingual

Math

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

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

Questions

Which is better, GPT-4.1 mini or Qwen3.7 Plus?

Which is better for coding, GPT-4.1 mini or Qwen3.7 Plus?

Which is better for agentic tasks, GPT-4.1 mini or Qwen3.7 Plus?

Which costs less, GPT-4.1 mini or Qwen3.7 Plus?

Which has the larger context window, GPT-4.1 mini or Qwen3.7 Plus?

Related comparisons

Watch GPT-4.1 mini vs Qwen3.7 Plus