DeepSeek V3 vs Qwen3-235B-A22B
DeepSeek V3 (2024) and Qwen3-235B-A22B (2025) are compact production models from DeepSeek and Alibaba. DeepSeek V3 ships a 64k-token context window, while Qwen3-235B-A22B ships a 128k-token context window. On MMLU PRO, Qwen3-235B-A22B leads by 6.9 pts. On pricing, Qwen3-235B-A22B costs $0.09/1M input tokens versus $0.10/1M 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.
Pick Qwen3-235B-A22B for general evaluation; DeepSeek V3 is better when provider fit matters more.
Decision scorecard
Local evidence first| Signal | DeepSeek V3 | Qwen3-235B-A22B |
|---|---|---|
| Best for | tool-calling agents and provider-routed production | provider-routed production |
| Decision fit | Coding, Agents, and Classification | Coding, RAG, and Long context |
| Context window | 64k | 128k |
| Cheapest output | $0.30/1M tokens | $0.58/1M tokens |
| Provider routes | 13 tracked | 5 tracked |
| Shared benchmarks | 4 rows | MMLU PRO leader |
Decision tradeoffs
- DeepSeek V3 has the lower cheapest tracked output price at $0.30/1M tokens.
- DeepSeek V3 has broader tracked provider coverage for fallback and procurement flexibility.
- DeepSeek V3 uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags DeepSeek V3 for Coding, Agents, and Classification.
- Qwen3-235B-A22B holds a shared-benchmark lead on MMLU PRO, ahead by 6.9 points.
- Qwen3-235B-A22B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Qwen3-235B-A22B for Coding, RAG, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
DeepSeek V3
$155
Cheapest tracked route/tier: Bitdeer AI
Qwen3-235B-A22B
$217
Cheapest tracked route/tier: Novita AI
Estimated monthly gap: $62.00. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI, AWS Bedrock, and OpenRouter; start route-level A/B tests there.
- Qwen3-235B-A22B is $0.28/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- Provider overlap exists on Fireworks AI, OpenRouter, and AWS Bedrock; start route-level A/B tests there.
- DeepSeek V3 is $0.28/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- DeepSeek V3 adds Function calling and Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-12-26 | 2025-04-29 |
| Context window | 64k | 128k |
| Parameters | 671B | 235B |
| Architecture | mixture of experts | decoder only |
| License | MIT(OSI) | Apache 2.0(OSI) |
| Openness | Open source | Open source |
| Commercial use | Commercial use allowed | Commercial use allowed |
| Knowledge cutoff | 2024-04 | - |
Pricing and availability
| Pricing attribute | DeepSeek V3 | Qwen3-235B-A22B |
|---|---|---|
| Input price | $0.10/1M tokens | $0.09/1M tokens |
| Output price | $0.30/1M tokens | $0.58/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3 | Qwen3-235B-A22B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | DeepSeek V3 | Qwen3-235B-A22B |
|---|---|---|
| MMLU PRO | 75.9 | 82.8 |
| LiveCodeBench | 49.6 | 80.4 |
| HumanEval | 85.5 | 92.7 |
| Aider Polyglot | 48.4 | 59.6 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek V3 at 75.9 and Qwen3-235B-A22B at 82.8, with Qwen3-235B-A22B ahead by 6.9 points; LiveCodeBench has DeepSeek V3 at 49.6 and Qwen3-235B-A22B at 80.4, with Qwen3-235B-A22B ahead by 30.8 points; HumanEval has DeepSeek V3 at 85.5 and Qwen3-235B-A22B at 92.7, with Qwen3-235B-A22B ahead by 7.2 points. The largest visible gap is 30.8 points on LiveCodeBench, 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 function calling: DeepSeek V3 and tool use: DeepSeek V3. Both models share 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 V3 lists $0.10/1M input and $0.30/1M output tokens on the cheapest tracked provider, while Qwen3-235B-A22B lists $0.09/1M input and $0.58/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3 lower by about $0.08 per million blended tokens. Availability is 13 providers versus 5, so concentration risk also matters.
Choose DeepSeek V3 when provider fit and broader provider choice are central to the workload. Choose Qwen3-235B-A22B when long-context analysis, larger context windows, and lower input-token cost 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 or Qwen3-235B-A22B?
Qwen3-235B-A22B supports 128k tokens, while DeepSeek V3 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.
Which is cheaper, DeepSeek V3 or Qwen3-235B-A22B?
DeepSeek V3 is cheaper on tracked token pricing. DeepSeek V3 costs $0.10/1M input and $0.30/1M output tokens. Qwen3-235B-A22B costs $0.09/1M input and $0.58/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3 or Qwen3-235B-A22B open source?
DeepSeek V3 is listed under MIT. Qwen3-235B-A22B 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 function calling, DeepSeek V3 or Qwen3-235B-A22B?
DeepSeek V3 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.
Which is better for tool use, DeepSeek V3 or Qwen3-235B-A22B?
DeepSeek V3 has the clearer documented tool use signal in this comparison. If tool use 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 and Qwen3-235B-A22B?
DeepSeek V3 is available on DeepInfra, Fireworks AI, DeepSeek Platform, Microsoft Foundry, and OpenRouter. Qwen3-235B-A22B is available on Fireworks AI, AWS Bedrock, OpenRouter, Venice AI, 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.