Model comparison

LFM2.5-2.6B vs Qwen3.7 Plus

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

LFM2.5-2.6B

LiquidAI

—

Evidence status unavailable

90% interval unavailable

Qwen3.7 Plus

Alibaba

66.2/100

Supported · Public rank #27

90% interval 56.8–75.5

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

3 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.

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
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
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. LFM2.5-2.6B does not fit this workload in one request. LFM2.5-2.6B 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.

4 LFM2.5-2.6B only

3 Shared

48 Qwen3.7 Plus only

Shared results: 3
LFM2.5-2.6B only: 4
Qwen3.7 Plus only: 48
Like-for-like categories: 0 / 8

1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.

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.

Instruction following

Directional only

LFM2.5-2.6B: 59.2
Qwen3.7 Plus: 84.5
Weighted basis: 1 vs 2 rows
Reading: Directional only

Agentic

Not comparable

LFM2.5-2.6B: Not measured
Qwen3.7 Plus: 71.7
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Coding

Not comparable

LFM2.5-2.6B: Not measured
Qwen3.7 Plus: 75.6
Weighted basis: 0 vs 4 rows
Reading: Not comparable

Reasoning

Not comparable

LFM2.5-2.6B: Not measured
Qwen3.7 Plus: 91.7
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Knowledge

Not comparable

LFM2.5-2.6B: Not measured
Qwen3.7 Plus: 60.1
Weighted basis: 0 vs 4 rows
Reading: Not comparable

Math

Not comparable

LFM2.5-2.6B: Not measured
Qwen3.7 Plus: 92.9
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Multilingual

Not comparable

LFM2.5-2.6B: Not measured
Qwen3.7 Plus: 85.4
Weighted basis: 0 vs 1 rows
Reading: Not comparable

Multimodal

Not comparable

LFM2.5-2.6B: Not measured
Qwen3.7 Plus: 81.5
Weighted basis: 0 vs 2 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for LFM2.5-2.6B and Qwen3.7 Plus
Category	LFM2.5-2.6B	Qwen3.7 Plus	Weighted basis	Reading
Instruction following	59.2	84.5	Directional only1 vs 2 rows	Directional only
Agentic	Not measured	71.7	Not comparable0 vs 2 rows	Not comparable
Coding	Not measured	75.6	Not comparable0 vs 4 rows	Not comparable
Reasoning	Not measured	91.7	Not comparable0 vs 1 rows	Not comparable
Knowledge	Not measured	60.1	Not comparable0 vs 4 rows	Not comparable
Math	Not measured	92.9	Not comparable0 vs 1 rows	Not comparable
Multilingual	Not measured	85.4	Not comparable0 vs 1 rows	Not comparable
Multimodal	Not measured	81.5	Not comparable0 vs 2 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.

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.

IFBench
Instruction following
LFM2.5-2.6B: 59.2%Qwen3.7 Plus: 79.1%Normalized gap 19.9LFM2.5-2.6B 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

LFM2.5-2.6B: Self-hosted; infrastructure cost varies; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

LFM2.5-2.6B 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

LFM2.5-2.6B: Self-hosted; infrastructure cost varies; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

LFM2.5-2.6B 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

LFM2.5-2.6B: Self-hosted; infrastructure cost varies; 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

LFM2.5-2.6B does not fit this workload in one request. LFM2.5-2.6B 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.

SpecificationLFM2.5-2.6BQwen3.7 Plus

Context window

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

LFM2.5-2.6B

128K

LiquidAI Hugging Face model card

Qwen3.7 Plus

API model ID

LFM2.5-2.6B

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.

LFM2.5-2.6B

No comparable hosted API rate

LiquidAI Hugging Face model card

Qwen3.7 Plus

No comparable hosted API rate

Documented inputs

LFM2.5-2.6B

Not sourced

Qwen3.7 Plus

Not sourced

Documented outputs

LFM2.5-2.6B

Not sourced

Qwen3.7 Plus

Not sourced

Provider availability

LFM2.5-2.6B

Not sourced

Qwen3.7 Plus

Not sourced

Reasoning profile

LFM2.5-2.6B

Reasoning

Qwen3.7 Plus

Reasoning

Weight access

LFM2.5-2.6B

Open Weight

Qwen3.7 Plus

Proprietary

License

LFM2.5-2.6B

Open Weight

Qwen3.7 Plus

Proprietary

Release date

LFM2.5-2.6B

2026-08-04

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 evidence55 rows

Agentic

BFCL v4
LFM2.5-2.6B56.9%
Source
Qwen3.7 Plus72.9%
Source
Qwen3.7 Plus leads this result
τ³-bench results
LFM2.5-2.6B5.7%
Source
Qwen3.7 Plus—
Not directly comparable
Claw-Eval
LFM2.5-2.6B62.9%
Source
Qwen3.7 Plus62.7%
Source
LFM2.5-2.6B leads this result
PinchBench
LFM2.5-2.6B68.2%
Source
Qwen3.7 Plus—
Not directly comparable
Terminal-Bench 2.0
LFM2.5-2.6B—
Qwen3.7 Plus70.3%
Source
Not directly comparable
QwenClawBench
LFM2.5-2.6B—
Qwen3.7 Plus61.8%
Source
Not directly comparable
MCP Atlas
LFM2.5-2.6B—
Qwen3.7 Plus73.2%
Source
Not directly comparable
VITA-Bench
LFM2.5-2.6B—
Qwen3.7 Plus45.6%
Source
Not directly comparable
DeepPlanning
LFM2.5-2.6B—
Qwen3.7 Plus62.3%
Source
Not directly comparable
OSWorld-Verified
LFM2.5-2.6B—
Qwen3.7 Plus73.3%
Source
Not directly comparable
AndroidWorld
LFM2.5-2.6B—
Qwen3.7 Plus81.0%
Source
Not directly comparable
OSWorld 2.0
LFM2.5-2.6B—
Qwen3.7 Plus2.8%
Source
Not directly comparable

Coding

LiveCodeBench v6
LFM2.5-2.6B59.4%
Source
Qwen3.7 Plus—
Not directly comparable
Terminal-Bench 2.0
LFM2.5-2.6B—
Qwen3.7 Plus70.3%
Source
Not directly comparable
SWE-bench Verified
LFM2.5-2.6B—
Qwen3.7 Plus77.7%
Source
Not directly comparable
SWE-bench Pro
LFM2.5-2.6B—
Qwen3.7 Plus57.6%
Source
Not directly comparable
SWE Multilingual
LFM2.5-2.6B—
Qwen3.7 Plus75.8%
Source
Not directly comparable
NL2Repo
LFM2.5-2.6B—
Qwen3.7 Plus41.1%
Source
Not directly comparable
SciCode
LFM2.5-2.6B—
Qwen3.7 Plus51.3%
Source
Not directly comparable
LiveCodeBench
LFM2.5-2.6B—
Qwen3.7 Plus89.6%
Source
Not directly comparable

Reasoning

CritPt
LFM2.5-2.6B—
Qwen3.7 Plus9.1%
Source
Not directly comparable
MRCRv2
LFM2.5-2.6B—
Qwen3.7 Plus91.7%
Source
Not directly comparable

Knowledge

GPQA
LFM2.5-2.6B—
Qwen3.7 Plus90.3%
Source
Not directly comparable
GPQA-D
LFM2.5-2.6B—
Qwen3.7 Plus90.3%
Source
Not directly comparable
HLE
LFM2.5-2.6B—
Qwen3.7 Plus34.7%
Source
Not directly comparable
MMLU-Pro
LFM2.5-2.6B—
Qwen3.7 Plus88.5%
Source
Not directly comparable
MMLU-Redux
LFM2.5-2.6B—
Qwen3.7 Plus94.5%
Source
Not directly comparable
SuperGPQA
LFM2.5-2.6B—
Qwen3.7 Plus71.4%
Source
Not directly comparable
MMMLU
LFM2.5-2.6B—
Qwen3.7 Plus89.0%
Source
Not directly comparable

Math

AIME 2025
LFM2.5-2.6B51.9%
Source
Qwen3.7 Plus—
Not directly comparable
HMMT Feb 2026
LFM2.5-2.6B—
Qwen3.7 Plus92.9%
Source
Not directly comparable
IMOAnswerBench
LFM2.5-2.6B—
Qwen3.7 Plus86.0%
Source
Not directly comparable
Apex
LFM2.5-2.6B—
Qwen3.7 Plus22.7%
Source
Not directly comparable

Multilingual

MMLU-ProX
LFM2.5-2.6B—
Qwen3.7 Plus85.4%
Source
Not directly comparable
NOVA-63
LFM2.5-2.6B—
Qwen3.7 Plus58.8%
Source
Not directly comparable
INCLUDE
LFM2.5-2.6B—
Qwen3.7 Plus83.0%
Source
Not directly comparable
MAXIFE
LFM2.5-2.6B—
Qwen3.7 Plus88.8%
Source
Not directly comparable
PolyMath
LFM2.5-2.6B—
Qwen3.7 Plus84.0%
Source
Not directly comparable

Multimodal

MMMU-Pro
LFM2.5-2.6B—
Qwen3.7 Plus79%
Source
Not directly comparable
MathVision
LFM2.5-2.6B—
Qwen3.7 Plus90.3%
Source
Not directly comparable
CharXiv
LFM2.5-2.6B—
Qwen3.7 Plus85.9%
Source
Not directly comparable
ERQA
LFM2.5-2.6B—
Qwen3.7 Plus69.8%
Source
Not directly comparable
MedXpertQA (MM)
LFM2.5-2.6B—
Qwen3.7 Plus71.0%
Source
Not directly comparable
ScreenSpot Pro
LFM2.5-2.6B—
Qwen3.7 Plus79.0%
Source
Not directly comparable
SimpleVQA
LFM2.5-2.6B—
Qwen3.7 Plus81.7%
Source
Not directly comparable
MMSearch-Plus
LFM2.5-2.6B—
Qwen3.7 Plus41.4%
Source
Not directly comparable
RealWorldQA
LFM2.5-2.6B—
Qwen3.7 Plus86.9%
Source
Not directly comparable
OmniDocBench 1.5
LFM2.5-2.6B—
Qwen3.7 Plus91.4%
Source
Not directly comparable
OCRBench V2
LFM2.5-2.6B—
Qwen3.7 Plus70.7%
Source
Not directly comparable
ODINW13
LFM2.5-2.6B—
Qwen3.7 Plus51.1%
Source
Not directly comparable
Video-MME (with subtitle)
LFM2.5-2.6B—
Qwen3.7 Plus88.0%
Source
Not directly comparable
VideoMMMU
LFM2.5-2.6B—
Qwen3.7 Plus85.4%
Source
Not directly comparable
MLVU (M-Avg)
LFM2.5-2.6B—
Qwen3.7 Plus87.4%
Source
Not directly comparable

Instruction following

IFBench
LFM2.5-2.6B59.2%
Source
Qwen3.7 Plus79.1%
Source
Qwen3.7 Plus leads this result
IFEval
LFM2.5-2.6B—
Qwen3.7 Plus94.6%
Source
Not directly comparable

Frequently asked questions

Which is better, LFM2.5-2.6B 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, LFM2.5-2.6B or Qwen3.7 Plus?

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, LFM2.5-2.6B or Qwen3.7 Plus?

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, LFM2.5-2.6B 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, LFM2.5-2.6B 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 August 4, 2026

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LFM2.5-2.6B 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

Instruction following

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

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, LFM2.5-2.6B or Qwen3.7 Plus?

Which is better for coding, LFM2.5-2.6B or Qwen3.7 Plus?

Which is better for agentic tasks, LFM2.5-2.6B or Qwen3.7 Plus?

Which costs less, LFM2.5-2.6B or Qwen3.7 Plus?

Which has the larger context window, LFM2.5-2.6B or Qwen3.7 Plus?

Related comparisons

Watch LFM2.5-2.6B vs Qwen3.7 Plus