DeepSeek V3.1 vs Qwen3.6-35B-A3B
DeepSeek V3.1 (2026) and Qwen3.6-35B-A3B (2026) are agentic coding models from DeepSeek and Alibaba. DeepSeek V3.1 ships a 64K-token context window, while Qwen3.6-35B-A3B ships a 262K-token context window. On MMLU PRO, Qwen3.6-35B-A3B leads by 1.9 pts. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
Qwen3.6-35B-A3B fits 4x more tokens; pick it for long-context work and DeepSeek V3.1 for tighter calls.
Specs
| Released | 2026-03-01 | 2026-04-16 |
| Context window | 64K | 262K |
| Parameters | — | 35 |
| Architecture | mixture of experts | moe |
| License | Open Source | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| DeepSeek V3.1 | Qwen3.6-35B-A3B | |
|---|---|---|
| Input price | $0.56/1M tokens | - |
| Output price | $1.68/1M tokens | - |
| Providers | - |
Capabilities
| DeepSeek V3.1 | Qwen3.6-35B-A3B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | DeepSeek V3.1 | Qwen3.6-35B-A3B |
|---|---|---|
| MMLU PRO | 83.3 | 85.2 |
| SWE-bench Verified | 66.0 | 73.4 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek V3.1 at 83.3 and Qwen3.6-35B-A3B at 85.2, with Qwen3.6-35B-A3B ahead by 1.9 points; SWE-bench Verified has DeepSeek V3.1 at 66 and Qwen3.6-35B-A3B at 73.4, with Qwen3.6-35B-A3B ahead by 7.4 points. The largest visible gap is 7.4 points on SWE-bench Verified, 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 vision: DeepSeek V3.1, function calling: Qwen3.6-35B-A3B, tool use: Qwen3.6-35B-A3B, structured outputs: DeepSeek V3.1, and code execution: DeepSeek V3.1. Both models share multimodal input, 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: DeepSeek V3.1 has $0.56/1M input tokens and Qwen3.6-35B-A3B has no token price sourced yet. Provider availability is 6 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose DeepSeek V3.1 when coding workflow support and broader provider choice are central to the workload. Choose Qwen3.6-35B-A3B when coding workflow support 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, DeepSeek V3.1 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B supports 262K tokens, while DeepSeek V3.1 supports 64K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Is DeepSeek V3.1 or Qwen3.6-35B-A3B open source?
DeepSeek V3.1 is listed under Open Source. Qwen3.6-35B-A3B 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, DeepSeek V3.1 or Qwen3.6-35B-A3B?
DeepSeek V3.1 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, DeepSeek V3.1 or Qwen3.6-35B-A3B?
Both DeepSeek V3.1 and Qwen3.6-35B-A3B expose multimodal input. 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.
Which is better for function calling, DeepSeek V3.1 or Qwen3.6-35B-A3B?
Qwen3.6-35B-A3B 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 DeepSeek V3.1 and Qwen3.6-35B-A3B?
DeepSeek V3.1 is available on Microsoft Foundry, Fireworks AI, NVIDIA NIM, Together AI, and AWS Bedrock. Qwen3.6-35B-A3B 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: 2026-04-24. Data sourced from public model cards and provider documentation.