Together AI - Gemma 3n-e4B vs Qwen3.5-397B-A17B
Together AI - Gemma 3n-e4B (2026) and Qwen3.5-397B-A17B (2026) are frontier reasoning models from Google DeepMind and Alibaba. Together AI - Gemma 3n-e4B ships a 8K-token context window, while Qwen3.5-397B-A17B ships a 262K-token context window. On pricing, Together AI - Gemma 3n-e4B costs $0.02/1M input tokens versus $0.39/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Together AI - Gemma 3n-e4B is ~1850% cheaper at $0.02/1M; pay for Qwen3.5-397B-A17B only for reasoning depth.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2026-02-16 |
| Context window | 8K | 262K |
| Parameters | 4B | 397B |
| Architecture | decoder only | MoE |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | Together AI - Gemma 3n-e4B | Qwen3.5-397B-A17B |
|---|---|---|
| Input price | $0.02/1M tokens | $0.39/1M tokens |
| Output price | $0.04/1M tokens | $2.34/1M tokens |
| Providers |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | Qwen3.5-397B-A17B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on multimodal input: Qwen3.5-397B-A17B and reasoning mode: Qwen3.5-397B-A17B. Both models share function calling, tool use, and 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, Together AI - Gemma 3n-e4B lists $0.02/1M input and $0.04/1M 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 Together AI - Gemma 3n-e4B lower by about $0.95 per million blended tokens. Availability is 1 providers versus 1, so concentration risk also matters.
Choose Together AI - Gemma 3n-e4B when provider fit and lower input-token cost are central to the workload. Choose Qwen3.5-397B-A17B when reasoning depth 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. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, Together AI - Gemma 3n-e4B or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B supports 262K tokens, while Together AI - Gemma 3n-e4B 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, Together AI - Gemma 3n-e4B or Qwen3.5-397B-A17B?
Together AI - Gemma 3n-e4B is cheaper on tracked token pricing. Together AI - Gemma 3n-e4B costs $0.02/1M input and $0.04/1M 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 Together AI - Gemma 3n-e4B or Qwen3.5-397B-A17B open source?
Together AI - Gemma 3n-e4B 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, Together AI - Gemma 3n-e4B 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 reasoning mode, Together AI - Gemma 3n-e4B or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Together AI - Gemma 3n-e4B and Qwen3.5-397B-A17B?
Together AI - Gemma 3n-e4B is available on Together AI. Qwen3.5-397B-A17B is available on OpenRouter. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.