DeepSeek V3 vs Qwen2.5-72B
DeepSeek V3 (2024) and Qwen2.5-72B (2024) are compact production models from DeepSeek and Alibaba. DeepSeek V3 ships a 64k-token context window, while Qwen2.5-72B ships a 128k-token context window. On HumanEval, DeepSeek V3 leads by 26.4 pts. On pricing, DeepSeek V3 costs $0.10/1M 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.
DeepSeek V3 is ~100% cheaper at $0.10/1M; pay for Qwen2.5-72B only for long-context analysis.
Decision scorecard
Local evidence first| Signal | DeepSeek V3 | Qwen2.5-72B |
|---|---|---|
| Best for | tool-calling agents and provider-routed production | provider-routed production |
| Decision fit | Coding, Agents, and Classification | Coding, Long context, and Classification |
| Context window | 64k | 128k |
| Cheapest output | $0.30/1M tokens | $0.60/1M tokens |
| Provider routes | 13 tracked | 2 tracked |
| Shared benchmarks | HumanEval leader | 3 rows |
Decision tradeoffs
- DeepSeek V3 holds a shared-benchmark lead on HumanEval, ahead by 26.4 points.
- 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, Tool use, and Structured outputs in local model data.
- Local decision data tags DeepSeek V3 for Coding, Agents, and Classification.
- Qwen2.5-72B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Local decision data tags Qwen2.5-72B for Coding, Long context, and Classification.
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
Qwen2.5-72B
$310
Cheapest tracked route/tier: Bitdeer AI
Estimated monthly gap: $155. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI and Bitdeer AI; start route-level A/B tests there.
- Qwen2.5-72B is $0.30/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.
- Provider overlap exists on Fireworks AI and Bitdeer AI; start route-level A/B tests there.
- DeepSeek V3 is $0.30/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- DeepSeek V3 adds Function calling, Tool use, and Structured outputs in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-12-26 | 2024-06-07 |
| Context window | 64k | 128k |
| Parameters | 671B | 72.7B |
| 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 | Qwen2.5-72B |
|---|---|---|
| Input price | $0.10/1M tokens | $0.20/1M tokens |
| Output price | $0.30/1M tokens | $0.60/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3 | Qwen2.5-72B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| 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
| Benchmark | DeepSeek V3 | Qwen2.5-72B |
|---|---|---|
| HumanEval | 85.5 | 59.1 |
| HellaSwag | 95.7 | 87.6 |
| Massive Multitask Language Understanding | 88.5 | 86.1 |
Deep dive
On shared benchmark coverage, HumanEval has DeepSeek V3 at 85.5 and Qwen2.5-72B at 59.1, with DeepSeek V3 ahead by 26.4 points; HellaSwag has DeepSeek V3 at 95.7 and Qwen2.5-72B at 87.6, with DeepSeek V3 ahead by 8.1 points; Massive Multitask Language Understanding has DeepSeek V3 at 88.5 and Qwen2.5-72B at 86.1, with DeepSeek V3 ahead by 2.4 points. The largest visible gap is 26.4 points on HumanEval, 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, tool use: DeepSeek V3, and structured outputs: DeepSeek V3. 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.
For cost, DeepSeek V3 lists $0.10/1M input and $0.30/1M output tokens on the cheapest tracked provider, while Qwen2.5-72B lists $0.20/1M input and $0.60/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3 lower by about $0.16 per million blended tokens. Availability is 13 providers versus 2, so concentration risk also matters.
Choose DeepSeek V3 when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Qwen2.5-72B 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 V3 or Qwen2.5-72B?
Qwen2.5-72B 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 Qwen2.5-72B?
DeepSeek V3 is cheaper on tracked token pricing. DeepSeek V3 costs $0.10/1M input and $0.30/1M output tokens. Qwen2.5-72B costs $0.20/1M input and $0.60/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3 or Qwen2.5-72B open source?
DeepSeek V3 is listed under MIT. Qwen2.5-72B 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 Qwen2.5-72B?
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 Qwen2.5-72B?
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 Qwen2.5-72B?
DeepSeek V3 is available on DeepInfra, Fireworks AI, DeepSeek Platform, Microsoft Foundry, and OpenRouter. Qwen2.5-72B is available on Fireworks AI and Bitdeer 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.