Model comparison
Gemma 4 vs Qwen3.6
- Input
- $0.12 / 1M tokens
- Output
- $0.35 / 1M tokens
- Context
- 256K
- Released
- 2026-04-02
- Input
- $0.2885 / 1M tokens
- Output
- $3.17 / 1M tokens
- Context
- 262K (extensible ~1M)
- Released
- 2026-04
Qwen3.6 scores higher on 3 of the 4 benchmarks both models report (the other leads on 1); Gemma 4 is cheaper on input tokens ($0.1 vs $0.3 per 1M, 2.4×); Qwen3.6 has the larger context window (262K vs 256K).
Specs and pricing side by side
| Spec | Gemma 4 | Qwen3.6 |
|---|---|---|
| Maker | Alibaba (Qwen) | |
| Released | 2026-04-02 | 2026-04 |
| Context window | 256K | 262K (extensible ~1M) |
| Max output | not published | ~32K (up to ~82K for complex reasoning) |
| Input price | $0.12 / 1M tokens | $0.2885 / 1M tokens |
| Output price | $0.35 / 1M tokens | $3.17 / 1M tokens |
| Parameters | 30.7B (31B dense flagship); family spans E2B/E4B on-device and 26B MoE (3.8B active) | 27B dense (Qwen3.6-27B); 35B total / 3B active MoE (Qwen3.6-35B-A3B) |
| License | Apache 2.0 | Apache 2.0same |
| Weights | Open weights | Open weightssame |
| Modalities | Text, Vision, Audio, Video | Text, Vision, Video |
| Knowledge cutoff | January 2025 | Not publicly disclosed |
Benchmarks both models report
| Benchmark | Gemma 4 | Qwen3.6 |
|---|---|---|
| AIME 2026 | 89.2% | 94.1% |
| GPQA Diamond | 84.3% | 87.8% |
| MMLU Pro | 85.2% | 86.2% |
| MMMU Pro | 76.9% | 75.8% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick Gemma 4 if…
- You care about MMMU Pro (it scores higher on 1 shared benchmark).
- Cost matters: input tokens cost 2.4× less ($0.1 vs $0.3 per 1M).
- You need Audio input, which Qwen3.6 lacks.
- Your use case is: self-hosted and on-premise LLM deployments where data must stay private.
Pick Qwen3.6 if…
- You care about AIME 2026, GPQA Diamond, MMLU Pro (it scores higher on 3 shared benchmarks).
- You need the longer context (262K vs 256K).
- Your use case is: agentic coding and repository-level software engineering (SWE-bench / Terminal-Bench style tasks).
FAQ
Which is better, Gemma 4 or Qwen3.6?
Qwen3.6 scores higher on 3 of the 4 benchmarks both models report (the other leads on 1); Gemma 4 is cheaper on input tokens ($0.1 vs $0.3 per 1M, 2.4×); Qwen3.6 has the larger context window (262K vs 256K). The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is Gemma 4?
Gemma 4: $0.12 / 1M tokens input, $0.35 / 1M tokens output. Qwen3.6: $0.2885 / 1M tokens input, $3.17 / 1M tokens output (list API prices as published by each maker).
What are the context windows of Gemma 4 and Qwen3.6?
Gemma 4 offers 256K; Qwen3.6 offers 262K (extensible ~1M) with up to ~32K (up to ~82K for complex reasoning) output.
Is Gemma 4 newer than Qwen3.6?
Gemma 4 was released 2026-04-02; Qwen3.6 was released 2026-04.