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Gemma 4 26B A4B vs Qwen3 235B A22B Instruct 2507

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Gemma 4 26B A4B and Qwen3 235B A22B Instruct 2507.

Google

Gemma 4 26B A4B

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference โ€” delivering near-31B quality at...

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Alibaba

Qwen3 235B A22B Instruct 2507

Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...

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Technical Specifications

SpecificationGemma 4 26B A4BQwen3 235B A22B Instruct 2507
ProviderGoogleAlibaba
Context Window262,144 tokens262,144 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-032025-07-21

API Pricing Comparison

Input Price per Million Tokens

Gemma 4 26B A4B

$0.06

Qwen3 235B A22B Instruct 2507

$0.09

Output Price per Million Tokens

Gemma 4 26B A4B

$0.33

Qwen3 235B A22B Instruct 2507

$0.10

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Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

Gemma 4 26B A4B Quirks & Gotchas

No developer gotchas reported.

Qwen3 235B A22B Instruct 2507 Quirks & Gotchas

No developer gotchas reported.