Gemma 4 26B A4B vs Qwen3.7 Plus

Updated October 20, 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 score estimate, 53.74 versus 45.61, but the 90% score intervals overlap. Treat that as a lead, not a settled winner. 6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

Model A

Gemma 4 26B A4B

Google

45.61/100

Supported · Public rank #117

90% interval 30.9–60.3

Model B

Qwen3.7 Plus

Alibaba

53.74/100

Supported · Public rank #77

90% interval 42.7–64.8

Shared results: 6
Gemma 4 26B A4B only: 3
Qwen3.7 Plus only: 47
Like-for-like categories: 0 / 8

Supported: Gemma 4 26B A4B and Qwen3.7 PlusHow 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.

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
Qwen3.7 Plus is 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
Gemma 4 26B A4B is not ranked on the public lane for agentic, so no winner is named for agentic.
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
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.

30.9Gemma 4 26B A4B40.3Qwen3.7 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

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.

MRCRv2Reasoning
Normalized gap 47.6
Gemma 4 26B A4B:44.1%
Qwen3.7 Plus:91.7%
Gemma 4 26B A4B source Qwen3.7 Plus source
HLEKnowledge
Normalized gap 17.5
Gemma 4 26B A4B:17.2%
Qwen3.7 Plus:34.7%
Gemma 4 26B A4B source Qwen3.7 Plus source
GPQAKnowledge
Normalized gap 8.0
Gemma 4 26B A4B:82.3%
Qwen3.7 Plus:90.3%
Gemma 4 26B A4B source Qwen3.7 Plus source
MMLU-ProKnowledge
Normalized gap 5.9
Gemma 4 26B A4B:82.6%
Qwen3.7 Plus:88.5%
Gemma 4 26B A4B source Qwen3.7 Plus source
MMMU-ProMultimodal
Normalized gap 5.2
Gemma 4 26B A4B:73.8%
Qwen3.7 Plus:79%
Gemma 4 26B A4B 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, 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

Gemma 4 26B A4B: 30.9; Supported · #94/152
Qwen3.7 Plus: 40.3; Estimated · #66/152
Basis: BenchAlign v5.8 lane · 1 vs 7 public rows
Reading: Directional only

Multimodal

Directional only

Gemma 4 26B A4B: 66.9; #40/55
Qwen3.7 Plus: 82.0; #16/55
Basis: Provisional lane · 1 vs 2 weighted rows
Reading: Directional only

Knowledge

Directional only

Gemma 4 26B A4B: 39.9; Estimated · #121/187
Qwen3.7 Plus: 53.7; Estimated · #67/187
Basis: BenchAlign v5.8 lane · 4 vs 7 public rows
Reading: Directional only

Instruction following

Directional only

Gemma 4 26B A4B: 88.7; #34/149
Qwen3.7 Plus: 92.8; #17/149
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Directional only

Agentic

Not comparable

Gemma 4 26B A4B: Not ranked
Qwen3.7 Plus: 35.1; Supported · #83/131
Basis: BenchAlign v5.8 lane · 0 vs 11 public rows
Reading: Not comparable

Reasoning

Not comparable

Gemma 4 26B A4B: 52.8; Unranked · 3 rankable rows
Qwen3.7 Plus: 80.0; Unranked · 3 rankable rows
Basis: Provisional lane · 1 vs 1 weighted rows
Reading: Not comparable

Multilingual

Not comparable

Gemma 4 26B A4B: Not ranked
Qwen3.7 Plus: 95.7; #3/17
Basis: Provisional lane · 0 vs 1 weighted rows
Reading: Not comparable

Math

Not comparable

Gemma 4 26B A4B: Not ranked
Qwen3.7 Plus: 64.3; Unranked · 4 rankable rows
Basis: Provisional lane · 0 vs 2 weighted rows
Reading: Not comparable

Category scores with the server-provided evidence basis for Gemma 4 26B A4B and Qwen3.7 Plus
Category	Gemma 4 26B A4B	Qwen3.7 Plus	Basis	Reading
Coding	30.9Supported · #94/152	40.3Estimated · #66/152	Directional onlyBenchAlign v5.8 lane · 1 vs 7 public rows	Directional only
Multimodal	66.9#40/55	82.0#16/55	Directional onlyProvisional lane · 1 vs 2 weighted rows	Directional only
Knowledge	39.9Estimated · #121/187	53.7Estimated · #67/187	Directional onlyBenchAlign v5.8 lane · 4 vs 7 public rows	Directional only
Instruction following	88.7#34/149	92.8#17/149	Directional onlyProvisional lane · 0 vs 1 weighted rows	Directional only
Agentic	Not ranked	35.1Supported · #83/131	Not comparableBenchAlign v5.8 lane · 0 vs 11 public rows	Not comparable
Reasoning	52.8Unranked · 3 rankable rows	80.0Unranked · 3 rankable rows	Not comparableProvisional lane · 1 vs 1 weighted rows	Not comparable
Multilingual	Not ranked	95.7#3/17	Not comparableProvisional lane · 0 vs 1 weighted rows	Not comparable
Math	Not ranked	64.3Unranked · 4 rankable rows	Not comparableProvisional lane · 0 vs 2 weighted rows	Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, 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

Gemma 4 26B A4B: Self-hosted; infrastructure cost varies; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

Gemma 4 26B A4B 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

Gemma 4 26B A4B: Self-hosted; infrastructure cost varies; Fits in one request
Qwen3.7 Plus: API rate not published; Fits in one request

Gemma 4 26B A4B 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

Gemma 4 26B A4B: Self-hosted; infrastructure cost varies; Fits in one request; Cached-input rate unavailable
Qwen3.7 Plus: API rate not published; Fits in one request; Cached-input rate unavailable

Gemma 4 26B A4B has no comparable published API token rate. 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

Qwen3.7 Plus

Reasoning

Weight access

Gemma 4 26B A4B

Open Weight

Qwen3.7 Plus

Proprietary

License

Gemma 4 26B A4B

Open Weight

Qwen3.7 Plus

Proprietary

Release date

Gemma 4 26B A4B

2026-04-02

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 estimate, 53.74 versus 45.61, but the 90% score intervals overlap.
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.

Questions

Which is better, Gemma 4 26B A4B or Qwen3.7 Plus?

Qwen3.7 Plus has the higher public score estimate, 53.74 versus 45.61, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Gemma 4 26B A4B or Qwen3.7 Plus?

Qwen3.7 Plus scores higher for coding on the public lane, 40.3 to 30.9. 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, Gemma 4 26B A4B or Qwen3.7 Plus?

Gemma 4 26B A4B is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Gemma 4 26B A4B 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, Gemma 4 26B A4B or Qwen3.7 Plus?

Qwen3.7 Plus has the larger documented context window: 1M, compared with 256K.

Self-host vs API cost

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

Gemma 4 26B A4B

API / mo$0

Self-host / mo$298

Break-even—

Qwen3.7 Plus

API / mo$0

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 evidence56 rows

Agentic

Terminal-Bench 2.0
Gemma 4 26B A4B—
Qwen3.7 Plus70.3%
Source
Not directly comparable
QwenClawBench
Gemma 4 26B A4B—
Qwen3.7 Plus61.8%
Source
Not directly comparable
Claw-Eval
Gemma 4 26B A4B—
Qwen3.7 Plus62.7%
Source
Not directly comparable
BFCL v4
Gemma 4 26B A4B—
Qwen3.7 Plus72.9%
Source
Not directly comparable
MCP Atlas
Gemma 4 26B A4B—
Qwen3.7 Plus73.2%
Source
Not directly comparable
VITA-Bench
Gemma 4 26B A4B—
Qwen3.7 Plus45.6%
Source
Not directly comparable
DeepPlanning
Gemma 4 26B A4B—
Qwen3.7 Plus62.3%
Source
Not directly comparable
OSWorld-Verified
Gemma 4 26B A4B—
Qwen3.7 Plus73.3%
Source
Not directly comparable
AndroidWorld
Gemma 4 26B A4B—
Qwen3.7 Plus81.0%
Source
Not directly comparable
OSWorld 2.0
Gemma 4 26B A4B—
Qwen3.7 Plus2.8%
Source
Not directly comparable
Terminal-Bench 2.1 (Vals)
Gemma 4 26B A4B—
Qwen3.7 Plus52.8%
Source
Not directly comparable

Coding

LiveCodeBench v6
Gemma 4 26B A4B77.1%
Source
Qwen3.7 Plus89.6%
Source
Qwen3.7 Plus leads this result
Terminal-Bench 2.0
Gemma 4 26B A4B—
Qwen3.7 Plus70.3%
Source
Not directly comparable
SWE-bench Verified
Gemma 4 26B A4B—
Qwen3.7 Plus77.7%
Source
Not directly comparable
SWE-bench Pro
Gemma 4 26B A4B—
Qwen3.7 Plus57.6%
Source
Not directly comparable
SWE Multilingual
Gemma 4 26B A4B—
Qwen3.7 Plus75.8%
Source
Not directly comparable
NL2Repo
Gemma 4 26B A4B—
Qwen3.7 Plus41.1%
Source
Not directly comparable
SciCode
Gemma 4 26B A4B—
Qwen3.7 Plus51.3%
Source
Not directly comparable

Reasoning

MRCRv2
Gemma 4 26B A4B44.1%
Source
Qwen3.7 Plus91.7%
Source
Qwen3.7 Plus leads this result
CritPt
Gemma 4 26B A4B—
Qwen3.7 Plus9.1%
Source
Not directly comparable

Multimodal

ExtractBench (LlamaIndex)
Gemma 4 26B A4B70.27%
Source
Qwen3.7 Plus—
Not directly comparable
ParseBench
Gemma 4 26B A4B58.50%
Source
Qwen3.7 Plus—
Not directly comparable
MMMU-Pro
Gemma 4 26B A4B73.8%
Source
Qwen3.7 Plus79%
Source
Qwen3.7 Plus leads this result
MathVision
Gemma 4 26B A4B—
Qwen3.7 Plus90.3%
Source
Not directly comparable
CharXiv
Gemma 4 26B A4B—
Qwen3.7 Plus85.9%
Source
Not directly comparable
ERQA
Gemma 4 26B A4B—
Qwen3.7 Plus69.8%
Source
Not directly comparable
MedXpertQA (MM)
Gemma 4 26B A4B—
Qwen3.7 Plus71.0%
Source
Not directly comparable
ScreenSpot Pro
Gemma 4 26B A4B—
Qwen3.7 Plus79.0%
Source
Not directly comparable
SimpleVQA
Gemma 4 26B A4B—
Qwen3.7 Plus81.7%
Source
Not directly comparable
MMSearch-Plus
Gemma 4 26B A4B—
Qwen3.7 Plus41.4%
Source
Not directly comparable
RealWorldQA
Gemma 4 26B A4B—
Qwen3.7 Plus86.9%
Source
Not directly comparable
OmniDocBench 1.5
Gemma 4 26B A4B—
Qwen3.7 Plus91.4%
Source
Not directly comparable
OCRBench V2
Gemma 4 26B A4B—
Qwen3.7 Plus70.7%
Source
Not directly comparable
ODINW13
Gemma 4 26B A4B—
Qwen3.7 Plus51.1%
Source
Not directly comparable
Video-MME (with subtitle)
Gemma 4 26B A4B—
Qwen3.7 Plus88.0%
Source
Not directly comparable
VideoMMMU
Gemma 4 26B A4B—
Qwen3.7 Plus85.4%
Source
Not directly comparable
MLVU (M-Avg)
Gemma 4 26B A4B—
Qwen3.7 Plus87.4%
Source
Not directly comparable

Knowledge

GPQA
Gemma 4 26B A4B82.3%
Source
Qwen3.7 Plus90.3%
Source
Qwen3.7 Plus leads this result
MMLU-Pro
Gemma 4 26B A4B82.6%
Source
Qwen3.7 Plus88.5%
Source
Qwen3.7 Plus leads this result
HLE
Gemma 4 26B A4B17.2%
Source
Qwen3.7 Plus34.7%
Source
Qwen3.7 Plus leads this result
HLE w/o tools
Gemma 4 26B A4B8.7%
Source
Qwen3.7 Plus—
Not directly comparable
GPQA-D
Gemma 4 26B A4B—
Qwen3.7 Plus90.3%
Source
Not directly comparable
MMLU-Redux
Gemma 4 26B A4B—
Qwen3.7 Plus94.5%
Source
Not directly comparable
SuperGPQA
Gemma 4 26B A4B—
Qwen3.7 Plus71.4%
Source
Not directly comparable
MMMLU
Gemma 4 26B A4B—
Qwen3.7 Plus89.0%
Source
Not directly comparable

Multilingual

MMLU-ProX
Gemma 4 26B A4B—
Qwen3.7 Plus85.4%
Source
Not directly comparable
NOVA-63
Gemma 4 26B A4B—
Qwen3.7 Plus58.8%
Source
Not directly comparable
INCLUDE
Gemma 4 26B A4B—
Qwen3.7 Plus83.0%
Source
Not directly comparable
MAXIFE
Gemma 4 26B A4B—
Qwen3.7 Plus88.8%
Source
Not directly comparable
PolyMath
Gemma 4 26B A4B—
Qwen3.7 Plus84.0%
Source
Not directly comparable

Instruction following

IFEval
Gemma 4 26B A4B—
Qwen3.7 Plus94.6%
Source
Not directly comparable
IFBench
Gemma 4 26B A4B—
Qwen3.7 Plus79.1%
Source
Not directly comparable

Math

HMMT Feb 2026
Gemma 4 26B A4B—
Qwen3.7 Plus92.9%
Source
Not directly comparable
IMOAnswerBench
Gemma 4 26B A4B—
Qwen3.7 Plus86.0%
Source
Not directly comparable
Apex
Gemma 4 26B A4B—
Qwen3.7 Plus22.7%
Source
Not directly comparable
FrontierMath v2 (Tiers 1-3)
Gemma 4 26B A4B—
Qwen3.7 Plus34.386%
Source
Not directly comparable

56 public results · 6 shared

Related comparisons

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Last updated October 20, 2026

Gemma 4 26B A4B vs Qwen3.7 Plus

Decision reading

Which one for your work

Long documents

Coding work

Agentic work

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Which one for a specific job

What is actually comparable

Shape of the matched evidence

Category results, on a stated basis

Coding

Multimodal

Knowledge

Instruction following

Agentic

Reasoning

Multilingual

Math

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

If you already use one of these models

Questions

Which is better, Gemma 4 26B A4B or Qwen3.7 Plus?

Which is better for coding, Gemma 4 26B A4B or Qwen3.7 Plus?

Which is better for agentic tasks, Gemma 4 26B A4B or Qwen3.7 Plus?

Which costs less, Gemma 4 26B A4B or Qwen3.7 Plus?

Which has the larger context window, Gemma 4 26B A4B or Qwen3.7 Plus?

Self-host vs API cost

Benchmark evidence

Agentic

Coding

Reasoning

Multimodal

Knowledge

Multilingual

Instruction following

Math

Related comparisons

Watch Gemma 4 26B A4B vs Qwen3.7 Plus