Model A

JetBrains

—

Evidence status unavailable

90% interval unavailable

Mellum2-12B-A2.5B-Thinking vs Qwen3.7 Plus

Updated September 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

Qwen3.7 Plus

Alibaba

62.29/100

Supported · Public rank #60

90% interval 52.4–72.2

Decision reading

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.

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

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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.

Long documents
Prompts that approach the documented context limit
Qwen3.7 Plus
Qwen3.7 Plus has the larger documented context window.
Confidence: documented

Show secondary and unsupported calls

Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
Mellum2-12B-A2.5B-Thinking is not ranked on the public lane for coding, so no winner is named for coding.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
Mellum2-12B-A2.5B-Thinking is scored on Estimated evidence for agentic, so the reading is directional rather than like-for-like.
Confidence: limited
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
The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. Mellum2-12B-A2.5B-Thinking does not fit this workload in one request. Mellum2-12B-A2.5B-Thinking has no comparable published API token rate. Qwen3.7 Plus has no comparable published API token rate.
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

What is actually comparable

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

1 Mellum2-12B-A2.5B-Thinking only

5 Shared

47 Qwen3.7 Plus only

Shared results: 5
Mellum2-12B-A2.5B-Thinking only: 1
Qwen3.7 Plus only: 47
Like-for-like categories: 0 / 8

2 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 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

Directional only

Mellum2-12B-A2.5B-Thinking: 48.3; Estimated · #76/151
Qwen3.7 Plus: 37.7; Supported · #126/151
Basis: BenchAlign lane · 1 vs 11 public rows
Reading: Directional only

Knowledge

Directional only

Mellum2-12B-A2.5B-Thinking: 48.8; Estimated · #96/181
Qwen3.7 Plus: 56.8; Estimated · #50/181
Basis: BenchAlign lane · 3 vs 7 public rows
Reading: Directional only

Coding

Not comparable

Mellum2-12B-A2.5B-Thinking: Not ranked
Qwen3.7 Plus: 53.1; Estimated · #51/183
Basis: BenchAlign lane · 1 vs 7 public rows
Reading: Not comparable

Reasoning

Not comparable

Mellum2-12B-A2.5B-Thinking: Not ranked
Qwen3.7 Plus: 73.7; Unranked · 3 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Mellum2-12B-A2.5B-Thinking: Not ranked
Qwen3.7 Plus: 78.3; Unranked · 3 rankable rows
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Mellum2-12B-A2.5B-Thinking: Not ranked
Qwen3.7 Plus: 78.9; #3/12
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Multimodal

Not comparable

Mellum2-12B-A2.5B-Thinking: Not ranked
Qwen3.7 Plus: 72.5; #18/48
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Instruction following

Not comparable

Mellum2-12B-A2.5B-Thinking: Not ranked
Qwen3.7 Plus: 91.1; #17/120
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Mellum2-12B-A2.5B-Thinking and Qwen3.7 Plus
Category	Mellum2-12B-A2.5B-Thinking	Qwen3.7 Plus	Basis	Reading
Agentic	48.3Estimated · #76/151	37.7Supported · #126/151	Directional onlyBenchAlign lane · 1 vs 11 public rows	Directional only
Knowledge	48.8Estimated · #96/181	56.8Estimated · #50/181	Directional onlyBenchAlign lane · 3 vs 7 public rows	Directional only
Coding	Not ranked	53.1Estimated · #51/183	Not comparableBenchAlign lane · 1 vs 7 public rows	Not comparable
Reasoning	Not ranked	73.7Unranked · 3 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	78.3Unranked · 3 rankable rows	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multilingual	Not ranked	78.9#3/12	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Multimodal	Not ranked	72.5#18/48	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable
Instruction following	Not ranked	91.1#17/120	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the 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.

GPQA
Knowledge
Mellum2-12B-A2.5B-Thinking: 57.6%Qwen3.7 Plus: 90.3%Normalized gap 32.7Mellum2-12B-A2.5B-Thinking 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

Mellum2-12B-A2.5B-Thinking: API rate not published; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

Mellum2-12B-A2.5B-Thinking has no comparable published API token rate. Qwen3.7 Plus has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

Mellum2-12B-A2.5B-Thinking: API rate not published; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

Mellum2-12B-A2.5B-Thinking has no comparable published API token rate. Qwen3.7 Plus has no comparable published API token rate.

Cache-heavy agent loop

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

Mellum2-12B-A2.5B-Thinking: API rate not published; Does not fit in one request; Cached-input rate unavailable
Qwen3.7 Plus: API rate not published; Fits in one request; Cached-input rate unavailable

Mellum2-12B-A2.5B-Thinking does not fit this workload in one request. Mellum2-12B-A2.5B-Thinking has no comparable published API token 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.

SpecificationMellum2-12B-A2.5B-ThinkingQwen3.7 Plus

Context window

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

Mellum2-12B-A2.5B-Thinking

128K

Qwen3.7 Plus

API model ID

Mellum2-12B-A2.5B-Thinking

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.

Mellum2-12B-A2.5B-Thinking

No comparable hosted API rate

Qwen3.7 Plus

No comparable hosted API rate

Documented inputs

Mellum2-12B-A2.5B-Thinking

Not sourced

Qwen3.7 Plus

Not sourced

Documented outputs

Mellum2-12B-A2.5B-Thinking

Not sourced

Qwen3.7 Plus

Not sourced

Provider availability

Mellum2-12B-A2.5B-Thinking

Not sourced

Qwen3.7 Plus

Not sourced

Reasoning profile

Mellum2-12B-A2.5B-Thinking

Reasoning

Qwen3.7 Plus

Reasoning

Weight access

Mellum2-12B-A2.5B-Thinking

Open Weight

Qwen3.7 Plus

Proprietary

License

Mellum2-12B-A2.5B-Thinking

Open Weight

Qwen3.7 Plus

Proprietary

Release date

Mellum2-12B-A2.5B-Thinking

2026-05-28

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: At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner.
Workload cost: A complete comparable API-rate estimate is not available for both models.
Context tradeoff: Qwen3.7 Plus 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 evidence53 rows

Agentic

BFCL v4
Mellum2-12B-A2.5B-Thinking45.6%
Source
Qwen3.7 Plus72.9%
Source
Qwen3.7 Plus leads this result
Terminal-Bench 2.0
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus70.3%
Source
Not directly comparable
QwenClawBench
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus61.8%
Source
Not directly comparable
Claw-Eval
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus62.7%
Source
Not directly comparable
MCP Atlas
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus73.2%
Source
Not directly comparable
VITA-Bench
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus45.6%
Source
Not directly comparable
DeepPlanning
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus62.3%
Source
Not directly comparable
OSWorld-Verified
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus73.3%
Source
Not directly comparable
AndroidWorld
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus81.0%
Source
Not directly comparable
OSWorld 2.0
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus2.8%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus52.8%
Source
Not directly comparable

Coding

LiveCodeBench v6
Mellum2-12B-A2.5B-Thinking69.9%
Source
Qwen3.7 Plus—
Not directly comparable
Terminal-Bench 2.0
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus70.3%
Source
Not directly comparable
SWE-bench Verified
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus77.7%
Source
Not directly comparable
SWE-bench Pro
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus57.6%
Source
Not directly comparable
SWE Multilingual
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus75.8%
Source
Not directly comparable
NL2Repo
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus41.1%
Source
Not directly comparable
SciCode
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus51.3%
Source
Not directly comparable
LiveCodeBench
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus89.6%
Source
Not directly comparable

Reasoning

CritPt
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus9.1%
Source
Not directly comparable
MRCRv2
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus91.7%
Source
Not directly comparable

Knowledge

MMLU-Redux
Mellum2-12B-A2.5B-Thinking86.2%
Source
Qwen3.7 Plus94.5%
Source
Qwen3.7 Plus leads this result
GPQA
Mellum2-12B-A2.5B-Thinking57.6%
Source
Qwen3.7 Plus90.3%
Source
Qwen3.7 Plus leads this result
GPQA-D
Mellum2-12B-A2.5B-Thinking57.6%
Source
Qwen3.7 Plus90.3%
Source
Qwen3.7 Plus leads this result
HLE
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus34.7%
Source
Not directly comparable
MMLU-Pro
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus88.5%
Source
Not directly comparable
SuperGPQA
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus71.4%
Source
Not directly comparable
MMMLU
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus89.0%
Source
Not directly comparable

Math

HMMT Feb 2026
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus92.9%
Source
Not directly comparable
IMOAnswerBench
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus86.0%
Source
Not directly comparable
Apex
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus22.7%
Source
Not directly comparable

Multilingual

MMLU-ProX
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus85.4%
Source
Not directly comparable
NOVA-63
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus58.8%
Source
Not directly comparable
INCLUDE
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus83.0%
Source
Not directly comparable
MAXIFE
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus88.8%
Source
Not directly comparable
PolyMath
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus84.0%
Source
Not directly comparable

Multimodal

MMMU-Pro
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus79%
Source
Not directly comparable
MathVision
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus90.3%
Source
Not directly comparable
CharXiv
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus85.9%
Source
Not directly comparable
ERQA
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus69.8%
Source
Not directly comparable
MedXpertQA (MM)
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus71.0%
Source
Not directly comparable
ScreenSpot Pro
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus79.0%
Source
Not directly comparable
SimpleVQA
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus81.7%
Source
Not directly comparable
MMSearch-Plus
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus41.4%
Source
Not directly comparable
RealWorldQA
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus86.9%
Source
Not directly comparable
OmniDocBench 1.5
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus91.4%
Source
Not directly comparable
OCRBench V2
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus70.7%
Source
Not directly comparable
ODINW13
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus51.1%
Source
Not directly comparable
Video-MME (with subtitle)
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus88.0%
Source
Not directly comparable
VideoMMMU
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus85.4%
Source
Not directly comparable
MLVU (M-Avg)
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus87.4%
Source
Not directly comparable

Instruction following

IFEval
Mellum2-12B-A2.5B-Thinking76.5%
Source
Qwen3.7 Plus94.6%
Source
Qwen3.7 Plus leads this result
IFBench
Mellum2-12B-A2.5B-Thinking—
Qwen3.7 Plus79.1%
Source
Not directly comparable

Frequently asked questions

Which is better, Mellum2-12B-A2.5B-Thinking or Qwen3.7 Plus?

At least one model is not scored in the current public ranking lane, so the page does not name an overall quality winner. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Mellum2-12B-A2.5B-Thinking or Qwen3.7 Plus?

Mellum2-12B-A2.5B-Thinking is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Mellum2-12B-A2.5B-Thinking or Qwen3.7 Plus?

Mellum2-12B-A2.5B-Thinking scores higher for agentic tasks on the public lane, 48.3 to 37.7. Mellum2-12B-A2.5B-Thinking is scored on Estimated evidence for agentic tasks, so the reading is directional rather than like-for-like. BenchLM does not name a winner for agentic tasks from a directional reading; read the shared benchmark rows directly and test the models on the same task set.

Which costs less, Mellum2-12B-A2.5B-Thinking 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, Mellum2-12B-A2.5B-Thinking or Qwen3.7 Plus?

Qwen3.7 Plus has the larger documented context window: 1M, compared with 128K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 4, 2026

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Mellum2-12B-A2.5B-Thinking vs Qwen3.7 Plus

Which one for your work

Long documents

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

What is actually comparable

Category results, on a stated basis

Agentic

Knowledge

Coding

Reasoning

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

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Frequently asked questions

Which is better, Mellum2-12B-A2.5B-Thinking or Qwen3.7 Plus?

Which is better for coding, Mellum2-12B-A2.5B-Thinking or Qwen3.7 Plus?

Which is better for agentic tasks, Mellum2-12B-A2.5B-Thinking or Qwen3.7 Plus?

Which costs less, Mellum2-12B-A2.5B-Thinking or Qwen3.7 Plus?

Which has the larger context window, Mellum2-12B-A2.5B-Thinking or Qwen3.7 Plus?

Related comparisons

Watch Mellum2-12B-A2.5B-Thinking vs Qwen3.7 Plus