Gemma 7B Instruct vs Qwen3.5-397B-A17B
Gemma 7B Instruct (2024) and Qwen3.5-397B-A17B (2026) are compact production models from Google DeepMind and Alibaba. Gemma 7B Instruct ships a 8K-token context window, while Qwen3.5-397B-A17B ships a 262K-token context window. On Google-Proof Q&A, Qwen3.5-397B-A17B leads by 38.5 pts. On pricing, Gemma 7B Instruct costs $0.05/1M input tokens versus $0.39/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Gemma 7B Instruct is ~680% cheaper at $0.05/1M; pay for Qwen3.5-397B-A17B only for long-context analysis.
Specs
| Released | 2024-02-21 | 2026-02-16 |
| Context window | 8K | 262K |
| Parameters | 7B | 397B |
| Architecture | decoder only | MoE |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | 2023-04 | - |
Pricing and availability
| Gemma 7B Instruct | Qwen3.5-397B-A17B | |
|---|---|---|
| Input price | $0.05/1M tokens | $0.39/1M tokens |
| Output price | $0.25/1M tokens | $2.34/1M tokens |
| Providers |
Capabilities
| Gemma 7B Instruct | Qwen3.5-397B-A17B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | Gemma 7B Instruct | Qwen3.5-397B-A17B |
|---|---|---|
| Google-Proof Q&A | 50.8 | 89.3 |
| Instruction-Following Evaluation | 42.6 | 92.6 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has Gemma 7B Instruct at 50.8 and Qwen3.5-397B-A17B at 89.3, with Qwen3.5-397B-A17B ahead by 38.5 points; Instruction-Following Evaluation has Gemma 7B Instruct at 42.6 and Qwen3.5-397B-A17B at 92.6, with Qwen3.5-397B-A17B ahead by 50.0 points. The largest visible gap is 50.0 points on Instruction-Following Evaluation, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on multimodal input: Qwen3.5-397B-A17B. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Gemma 7B Instruct lists $0.05/1M input and $0.25/1M output tokens, while Qwen3.5-397B-A17B lists $0.39/1M input and $2.34/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Gemma 7B Instruct lower by about $0.86 per million blended tokens. Availability is 8 providers versus 1, so concentration risk also matters.
Choose Gemma 7B Instruct when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen3.5-397B-A17B when long-context analysis and larger context windows are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Gemma 7B Instruct or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B supports 262K tokens, while Gemma 7B Instruct supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Gemma 7B Instruct or Qwen3.5-397B-A17B?
Gemma 7B Instruct is cheaper on tracked token pricing. Gemma 7B Instruct costs $0.05/1M input and $0.25/1M output tokens. Qwen3.5-397B-A17B costs $0.39/1M input and $2.34/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Gemma 7B Instruct or Qwen3.5-397B-A17B open source?
Gemma 7B Instruct is listed under Open Source. Qwen3.5-397B-A17B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for multimodal input, Gemma 7B Instruct or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for structured outputs, Gemma 7B Instruct or Qwen3.5-397B-A17B?
Both Gemma 7B Instruct and Qwen3.5-397B-A17B expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Where can I run Gemma 7B Instruct and Qwen3.5-397B-A17B?
Gemma 7B Instruct is available on NVIDIA NIM, Fireworks AI, Together AI, GCP Vertex AI, and Cloudflare Workers AI. Qwen3.5-397B-A17B is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.