Together AI - Gemma 3n-e4B vs Qwen3.5-4B-Instruct
Together AI - Gemma 3n-e4B (2026) and Qwen3.5-4B-Instruct (2025) are compact production models from Google DeepMind and Alibaba. Together AI - Gemma 3n-e4B ships a 8k-token context window, while Qwen3.5-4B-Instruct ships a 256k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.
Qwen3.5-4B-Instruct fits 31x more tokens; pick it for long-context work and Together AI - Gemma 3n-e4B for tighter calls.
Decision scorecard
Local evidence first| Signal | Together AI - Gemma 3n-e4B | Qwen3.5-4B-Instruct |
|---|---|---|
| Best for | tool-calling agents | multimodal apps |
| Decision fit | Agents, Classification, and JSON / Tool use | Long context and Vision |
| Context window | 8k | 256k |
| Cheapest output | $0.04/1M tokens | - |
| Provider routes | 1 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Together AI - Gemma 3n-e4B has broader tracked provider coverage for fallback and procurement flexibility.
- Together AI - Gemma 3n-e4B uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
- Local decision data tags Together AI - Gemma 3n-e4B for Agents, Classification, and JSON / Tool use.
- Qwen3.5-4B-Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-4B-Instruct uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Qwen3.5-4B-Instruct for Long context and Vision.
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
Qwen3.5-4B-Instruct
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Together AI - Gemma 3n-e4B and Qwen3.5-4B-Instruct; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.
- Qwen3.5-4B-Instruct adds Vision and Multimodal in local capability data.
- No overlapping tracked provider route is sourced for Qwen3.5-4B-Instruct and Together AI - Gemma 3n-e4B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
- Together AI - Gemma 3n-e4B adds Function calling, Tool use, and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-03-15 | 2025-11-12 |
| Context window | 8k | 256k |
| Parameters | 4B | 4B |
| Architecture | decoder only | - |
| License | Gemma | Apache 2.0(OSI) |
| Openness | Open weights | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2024-06 | - |
Pricing and availability
| Pricing attribute | Together AI - Gemma 3n-e4B | Qwen3.5-4B-Instruct |
|---|---|---|
| Input price | $0.02/1M tokens | - |
| Output price | $0.04/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | Qwen3.5-4B-Instruct |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | No |
| 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: Qwen3.5-4B-Instruct, multimodal input: Qwen3.5-4B-Instruct, function calling: Together AI - Gemma 3n-e4B, tool use: Together AI - Gemma 3n-e4B, and structured outputs: Together AI - Gemma 3n-e4B. Both models share the core language-model surface, 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.
Pricing coverage is uneven: Together AI - Gemma 3n-e4B has $0.02/1M input tokens and Qwen3.5-4B-Instruct has no token price sourced yet. Provider availability is 1 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose Together AI - Gemma 3n-e4B when provider fit and broader provider choice are central to the workload. Choose Qwen3.5-4B-Instruct 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. 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 Qwen3.5-4B-Instruct?
Qwen3.5-4B-Instruct supports 256k 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.
Is Together AI - Gemma 3n-e4B or Qwen3.5-4B-Instruct open source?
Together AI - Gemma 3n-e4B is listed under Gemma. Qwen3.5-4B-Instruct 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 Qwen3.5-4B-Instruct?
Qwen3.5-4B-Instruct 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 Qwen3.5-4B-Instruct?
Qwen3.5-4B-Instruct 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 function calling, Together AI - Gemma 3n-e4B or Qwen3.5-4B-Instruct?
Together AI - Gemma 3n-e4B has the clearer documented function calling signal in this comparison. If function calling 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 Qwen3.5-4B-Instruct?
Together AI - Gemma 3n-e4B is available on Together AI. Qwen3.5-4B-Instruct is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.