Together AI - Gemma 3n-e4B vs Qwen3.5-27B
Together AI - Gemma 3n-e4B (2026) and Qwen3.5-27B (2026) are frontier reasoning models from Google DeepMind and Alibaba. Together AI - Gemma 3n-e4B ships a 8k-token context window, while Qwen3.5-27B ships a 262k-token context window. On pricing, Together AI - Gemma 3n-e4B costs $0.02/1M input tokens versus $0.20/1M for the alternative. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Together AI - Gemma 3n-e4B is ~875% cheaper at $0.02/1M; pay for Qwen3.5-27B only for reasoning depth.
Decision scorecard
Local evidence first| Signal | Together AI - Gemma 3n-e4B | Qwen3.5-27B |
|---|---|---|
| Best for | tool-calling agents | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Agents, Classification, and JSON / Tool use | RAG, Agents, and Long context |
| Context window | 8k | 262k |
| Cheapest output | $0.04/1M tokens | $1.56/1M tokens |
| Provider routes | 1 tracked | 4 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Together AI - Gemma 3n-e4B has the lower cheapest tracked output price at $0.04/1M tokens.
- Local decision data tags Together AI - Gemma 3n-e4B for Agents, Classification, and JSON / Tool use.
- Qwen3.5-27B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-27B has broader tracked provider coverage for fallback and procurement flexibility.
- Qwen3.5-27B uniquely exposes Vision, Multimodal, and Reasoning in local model data.
- Local decision data tags Qwen3.5-27B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Together AI - Gemma 3n-e4B
$26.00
Cheapest tracked route/tier: Together AI
Qwen3.5-27B
$546
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $520. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- No overlapping tracked provider route is sourced for Together AI - Gemma 3n-e4B and Qwen3.5-27B; plan for SDK, billing, or endpoint changes.
- Qwen3.5-27B is $1.52/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Qwen3.5-27B adds Vision, Multimodal, and Reasoning in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-27B and Together AI - Gemma 3n-e4B; plan for SDK, billing, or endpoint changes.
- Together AI - Gemma 3n-e4B is $1.52/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2026-02-24 |
| Context window | 8k | 262k |
| Parameters | 4B | 27B |
| Architecture | decoder only | decoder only |
| License | Gemma | Apache 2.0 |
| Knowledge cutoff | 2024-06 | - |
Pricing and availability
| Pricing attribute | Together AI - Gemma 3n-e4B | Qwen3.5-27B |
|---|---|---|
| Input price | $0.02/1M tokens | $0.20/1M tokens |
| Output price | $0.04/1M tokens | $1.56/1M tokens |
| Providers |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | Qwen3.5-27B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Qwen3.5-27B, multimodal input: Qwen3.5-27B, and reasoning mode: Qwen3.5-27B. 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 on the cheapest tracked provider, while Qwen3.5-27B lists $0.20/1M input and $1.56/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Together AI - Gemma 3n-e4B lower by about $0.58 per million blended tokens. Availability is 1 providers versus 4, 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 Qwen3.5-27B when reasoning depth, larger context windows, and broader provider choice 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.
FAQ
Which has a larger context window, Together AI - Gemma 3n-e4B or Qwen3.5-27B?
Qwen3.5-27B 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 Qwen3.5-27B?
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. Qwen3.5-27B costs $0.20/1M input and $1.56/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Together AI - Gemma 3n-e4B or Qwen3.5-27B open source?
Together AI - Gemma 3n-e4B is listed under Gemma. Qwen3.5-27B 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 vision, Together AI - Gemma 3n-e4B or Qwen3.5-27B?
Qwen3.5-27B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, Together AI - Gemma 3n-e4B or Qwen3.5-27B?
Qwen3.5-27B 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.
Where can I run Together AI - Gemma 3n-e4B and Qwen3.5-27B?
Together AI - Gemma 3n-e4B is available on Together AI. Qwen3.5-27B is available on DeepInfra, OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.