DeepSeek R1 vs Qwen3.5-397B-A17B
DeepSeek R1 (2025) and Qwen3.5-397B-A17B (2026) are frontier-tier reasoning models from DeepSeek and Alibaba. DeepSeek R1 ships a 128k-token context window, while Qwen3.5-397B-A17B ships a 262k-token context window. On SWE-bench Verified, Qwen3.5-397B-A17B leads by 27 pts. On pricing, DeepSeek R1 costs $0.10/1M input tokens versus $0.39/1M 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.
DeepSeek R1 is ~290% cheaper at $0.10/1M; pay for Qwen3.5-397B-A17B only for long-context analysis.
Decision scorecard
Local evidence first| Signal | DeepSeek R1 | Qwen3.5-397B-A17B |
|---|---|---|
| Best for | reasoning-heavy apps and provider-routed production | reasoning-heavy apps, multimodal apps, and tool-calling agents |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 128k | 262k |
| Cheapest output | $0.30/1M tokens | $2.34/1M tokens |
| Provider routes | 14 tracked | 4 tracked |
| Shared benchmarks | 2 rows | SWE-bench Verified leader |
Decision tradeoffs
- DeepSeek R1 has the lower cheapest tracked output price at $0.30/1M tokens.
- DeepSeek R1 has broader tracked provider coverage for fallback and procurement flexibility.
- DeepSeek R1 uniquely exposes Code execution in local model data.
- Local decision data tags DeepSeek R1 for Coding, RAG, and Agents.
- Qwen3.5-397B-A17B holds a shared-benchmark lead on SWE-bench Verified, ahead by 27 points.
- Qwen3.5-397B-A17B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Qwen3.5-397B-A17B uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Qwen3.5-397B-A17B for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek R1
$155
Cheapest tracked route/tier: Bitdeer AI
Qwen3.5-397B-A17B
$897
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $742. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Together AI; start route-level A/B tests there.
- Qwen3.5-397B-A17B is $2.04/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Code execution before moving production traffic.
- Qwen3.5-397B-A17B adds Vision, Multimodal, and Function calling in local capability data.
- Provider overlap exists on OpenRouter and Together AI; start route-level A/B tests there.
- DeepSeek R1 is $2.04/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- DeepSeek R1 adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-20 | 2026-02-16 |
| Context window | 128k | 262k |
| Parameters | 671B, 37B Active | 397B |
| Architecture | decoder only | MoE |
| License | MIT(OSI) | Apache 2.0(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | 2023-12 | - |
Pricing and availability
| Pricing attribute | DeepSeek R1 | Qwen3.5-397B-A17B |
|---|---|---|
| Input price | $0.10/1M tokens | $0.39/1M tokens |
| Output price | $0.30/1M tokens | $2.34/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek R1 | Qwen3.5-397B-A17B |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | Yes | Yes |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek R1 | Qwen3.5-397B-A17B |
|---|---|---|
| SWE-bench Verified | 49.2 | 76.2 |
| Google-Proof Q&A | 71.5 | 89.3 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has DeepSeek R1 at 49.2 and Qwen3.5-397B-A17B at 76.2, with Qwen3.5-397B-A17B ahead by 27 points; Google-Proof Q&A has DeepSeek R1 at 71.5 and Qwen3.5-397B-A17B at 89.3, with Qwen3.5-397B-A17B ahead by 17.8 points. The largest visible gap is 27 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: Qwen3.5-397B-A17B, multimodal input: Qwen3.5-397B-A17B, function calling: Qwen3.5-397B-A17B, tool use: Qwen3.5-397B-A17B, and code execution: DeepSeek R1. Both models share reasoning mode 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, DeepSeek R1 lists $0.10/1M input and $0.30/1M output tokens on the cheapest tracked provider, 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 DeepSeek R1 lower by about $0.81 per million blended tokens. Availability is 14 providers versus 4, so concentration risk also matters.
Choose DeepSeek R1 when coding workflow support, 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, DeepSeek R1 or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B supports 262k tokens, while DeepSeek R1 supports 128k 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.
Which is cheaper, DeepSeek R1 or Qwen3.5-397B-A17B?
DeepSeek R1 is cheaper on tracked token pricing. DeepSeek R1 costs $0.10/1M input and $0.30/1M 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 DeepSeek R1 or Qwen3.5-397B-A17B open source?
DeepSeek R1 is listed under MIT. 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 vision, DeepSeek R1 or Qwen3.5-397B-A17B?
Qwen3.5-397B-A17B 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 R1 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.
Where can I run DeepSeek R1 and Qwen3.5-397B-A17B?
DeepSeek R1 is available on DeepSeek Platform, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. Qwen3.5-397B-A17B is available on OpenRouter, Together AI, Alibaba Cloud PAI-EAS, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.