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Model comparison

Gemma 4 26B A4B vs Qwen3.5 397B

Data verified

Head-to-head evidence from 19 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

57.96/100
Margin
1.0pts
← winning
57.01/100
0 category wins2 category wins

Public leaderboard positions: Gemma 4 26B A4B #67 (Supported); Qwen3.5 397B #71 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Gemma 4 26B A4B and Qwen3.5 397B share 19 comparable benchmark results. 2 of 8 categories are comparable. 1 result is unique to Gemma 4 26B A4B; 36 to Qwen3.5 397B.

Updated July 23, 2026
Shared results
19
Gemma 4 26B A4B only
1
Qwen3.5 397B only
36
Comparable categories
2 / 8

Pick Gemma 4 26B A4B if you want the stronger benchmark profile. Qwen3.5 397B only becomes the better choice if knowledge is the priority or you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 19 shared benchmark results across 6 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Gemma 4 26B A4B has the cleaner BenchAlign overall profile here, landing at 57.96 versus 57.01. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

Qwen3.5 397B is also the more expensive model on tokens at $0.60 input / $3.60 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Gemma 4 26B A4B. That is roughly Infinityx on output cost alone. Gemma 4 26B A4B is the reasoning model in the pair, while Qwen3.5 397B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Gemma 4 26B A4B gives you the larger context window at 256K, compared with 128K for Qwen3.5 397B.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Gemma 4 26B A4B and Qwen3.5 397B
CategoryGemma 4 26B A4BΔQwen3.5 397B
KnowledgeGemma 4 26B A4B43.4Margin 13.2Qwen3.5 397B56.6
MultimodalGemma 4 26B A4B73.8Margin 5.8Qwen3.5 397B79.6
AgenticGemma 4 26B A4BNot measuredMarginNo overlapQwen3.5 397B56.5
CodingGemma 4 26B A4BNot measuredMarginNo overlapQwen3.5 397B66.5
ReasoningGemma 4 26B A4BNot measuredMarginNo overlapQwen3.5 397B63.2
MathGemma 4 26B A4BNot measuredMarginNo overlapQwen3.5 397B90.6
MultilingualGemma 4 26B A4BNot measuredMarginNo overlapQwen3.5 397B84.7
Inst. FollowingGemma 4 26B A4BNot measuredMarginNo overlapQwen3.5 397B92.6

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Gemma 4 26B A4BB · Qwen3.5 397B
  1. HLE

    Knowledge
    Source ↗
    A 17.2%B 28.7%
    Winner: Qwen3.5 397BΔ 11.5
    HLE: Gemma 4 26B A4B scored 17.2%; Qwen3.5 397B scored 28.7%. Qwen3.5 397B wins this benchmark.
  2. MMLU-Pro

    Knowledge
    Source ↗
    A 82.6%B 87.8%
    Winner: Qwen3.5 397BΔ 5.2
    MMLU-Pro: Gemma 4 26B A4B scored 82.6%; Qwen3.5 397B scored 87.8%. Qwen3.5 397B wins this benchmark.
  3. MMMU-Pro

    Multimodal
    Source ↗
    A 73.8%B 79%
    Winner: Qwen3.5 397BΔ 5.2
    MMMU-Pro: Gemma 4 26B A4B scored 73.8%; Qwen3.5 397B scored 79%. Qwen3.5 397B wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGemma 4 26B A4BQwen3.5 397BComparison
Input / output priceUSD per 1M tokensGemma 4 26B A4B$0 input / $0 outputQwen3.5 397B$0.6 input / $3.6 outputGemma 4 26B A4B has the lower combined listed price.
Generation speedtokens per secondGemma 4 26B A4BNot availableQwen3.5 397B96 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenGemma 4 26B A4BNot availableQwen3.5 397B2.44 sA complete latency comparison is not available.
Context windowmaximum listed tokensGemma 4 26B A4B256KQwen3.5 397B128KGemma 4 26B A4B lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkGemma 4 26B A4BQwen3.5 397BResult
AA Agentic IndexSource 11.0%19.9%Qwen3.5 397B leads
τ²-bench resultsSource 43.6%95.6%Qwen3.5 397B leads
GDPval-AASource 13.1%23.1%Qwen3.5 397B leads
GDPval-AASource 761962Qwen3.5 397B leads
Terminal-Bench 2.0Source 52.5%Not comparable
BrowseCompSource 62%Not comparable
Claw-EvalSource 56.8%Not comparable
QwenClawBenchSource 51.8%Not comparable
τ³-bench resultsSource 68.4%Not comparable
VITA-BenchSource 43.7%Not comparable
DeepPlanningSource 37.6%Not comparable
ToolathlonSource 36.3%Not comparable
MCP AtlasSource 46.1%Not comparable
MCP-TasksSource 74.2%Not comparable
WideResearchSource 74.0%Not comparable
Gert LabsSource 46.76%Not comparable
ResearchClawBenchSource 14.2%Not comparable
APEX-Agents-AASource 15.3%Not comparable
Coding
BenchmarkGemma 4 26B A4BQwen3.5 397BResult
AA Coding IndexSource 39.3%48.2%Qwen3.5 397B leads
AA-SciCodeSource 40.0%42.0%Qwen3.5 397B leads
SWE-bench VerifiedSource 76.2%Not comparable
LiveCodeBench v6Source 83.6%Not comparable
SWE-bench ProSource 50.9%Not comparable
Reasoning
BenchmarkGemma 4 26B A4BQwen3.5 397BResult
AA-LCRSource 55.7%65.7%Qwen3.5 397B leads
CritPtSource 0.0%1.7%Qwen3.5 397B leads
LongBench v2Source 63.2%Not comparable
AI-NeedleSource 68.7%Not comparable
KnowledgeQwen3.5 397B wins
BenchmarkGemma 4 26B A4BQwen3.5 397BResult
MMLU-ProSource 82.6%87.8%Qwen3.5 397B leads
HLESource 17.2%28.7%Qwen3.5 397B leads
HLE w/o toolsSource 8.7%Not comparable
Artificial Analysis Intelligence IndexSource 25.7%33.7%Qwen3.5 397B leads
AA-GPQA DiamondSource 79.2%89.3%Qwen3.5 397B leads
AA-HLESource 18.3%27.3%Qwen3.5 397B leads
AA-Omniscience IndexSource -48.1%-29.8%Qwen3.5 397B leads
AA-Omniscience AccuracySource 18.2%31.4%Qwen3.5 397B leads
AA-Omniscience Hallucination RateSource 80.9%89.1%Gemma 4 26B A4B leads
GPQASource 88.4%Not comparable
SuperGPQASource 70.4%Not comparable
MMLU-ReduxSource 94.9%Not comparable
C-EvalSource 93%Not comparable
Math
BenchmarkGemma 4 26B A4BQwen3.5 397BResult
AIME26Source 93.3%Not comparable
HMMT Feb 2025Source 94.8%Not comparable
HMMT Nov 2025Source 92.7%Not comparable
HMMT Feb 2026Source 87.9%Not comparable
MMAnswerBenchSource 80.9%Not comparable
Multilingual
BenchmarkGemma 4 26B A4BQwen3.5 397BResult
MMLU-ProXSource 84.7%Not comparable
NOVA-63Source 59.1%Not comparable
MultimodalQwen3.5 397B wins
BenchmarkGemma 4 26B A4BQwen3.5 397BResult
MMMU-ProSource 73.8%79%Qwen3.5 397B leads
AA-MMMU-ProSource 69.2%77.3%Qwen3.5 397B leads
MathVisionSource 88.6%Not comparable
CharXivSource 80.8%Not comparable
VideoMMMUSource 84.7%Not comparable
ScreenSpot ProSource 65.6%Not comparable
V*Source 95.8%Not comparable
Inst. Following
BenchmarkGemma 4 26B A4BQwen3.5 397BResult
AA-IFBenchSource 72.4%78.8%Qwen3.5 397B leads
IFEvalSource 92.6%Not comparable
Frequently Asked Questions (3)

Which is better, Gemma 4 26B A4B or Qwen3.5 397B?

Gemma 4 26B A4B is ahead on BenchLM's BenchAlign leaderboard, 57.96 to 57.01. The biggest single separator in this matchup is HLE, where the scores are 17.2% and 28.7%.

Which is better for knowledge tasks, Gemma 4 26B A4B or Qwen3.5 397B?

Qwen3.5 397B has the edge for knowledge tasks in this comparison, averaging 56.6 versus 43.4. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, Gemma 4 26B A4B or Qwen3.5 397B?

Qwen3.5 397B has the edge for multimodal and grounded tasks in this comparison, averaging 79.6 versus 73.8. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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