DeepSeek V4 Pro vs Qwen2.5-72B-Instruct
DeepSeek V4 Pro (2026) and Qwen2.5-72B-Instruct (2024) are frontier reasoning models from DeepSeek and Alibaba. DeepSeek V4 Pro ships a 1M-token context window, while Qwen2.5-72B-Instruct ships a 128K-token context window. On Google-Proof Q&A, DeepSeek V4 Pro leads by 51.7 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
DeepSeek V4 Pro fits 8x more tokens; pick it for long-context work and Qwen2.5-72B-Instruct for tighter calls.
Decision scorecard
Local evidence first| Signal | DeepSeek V4 Pro | Qwen2.5-72B-Instruct |
|---|---|---|
| Best for | reasoning-heavy apps, tool-calling agents, and long-context analysis | provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Long context |
| Context window | 1M | 128K |
| Cheapest output | $0.73/1M tokens | $0.54/1M tokens |
| Provider routes | 6 tracked | 8 tracked |
| Shared benchmarks | Google-Proof Q&A leader | 4 shared |
Decision tradeoffs
- DeepSeek V4 Pro holds a shared-benchmark lead on Google-Proof Q&A, ahead by 51.7 points.
- DeepSeek V4 Pro has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek V4 Pro uniquely exposes Reasoning and JSON / Tool use in local model data.
- Local decision data tags DeepSeek V4 Pro for Coding, RAG, and Agents.
- Qwen2.5-72B-Instruct holds a shared-benchmark lead on HumanEval, ahead by 9.8 points.
- Qwen2.5-72B-Instruct has the lower cheapest tracked output price at $0.54/1M tokens.
- Qwen2.5-72B-Instruct has broader tracked provider coverage for fallback and route flexibility.
- Local decision data tags Qwen2.5-72B-Instruct 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 V4 Pro
$472
Cheapest tracked route/tier: OpenRouter
Qwen2.5-72B-Instruct
$279
Cheapest tracked route/tier: Chutes AI
Estimated monthly gap: $193. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter, Fireworks AI, and Novita AI; start route-level A/B tests there.
- Qwen2.5-72B-Instruct is $0.19/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning and JSON / Tool use before moving production traffic.
- Provider overlap exists on Fireworks AI, OpenRouter, and Novita AI; start route-level A/B tests there.
- DeepSeek V4 Pro is $0.19/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- DeepSeek V4 Pro adds Reasoning and JSON / Tool use in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2026-04-24 | 2024-06-07 |
| Context window | 1M | 128K |
| Parameters | 1.6T | 72.7B |
| Architecture | Mixture of Experts | Decoder Only |
| License | MITOSI-approved | Apache 2.0OSI-approved |
| Openness | Open source | Open source |
| Weights | Available | Available |
| Code | Unknown | Unknown |
| Commercial use | Permitted | Permitted |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | DeepSeek V4 Pro | Qwen2.5-72B-Instruct |
|---|---|---|
| Input price |
| $0.18/1M tokens |
| Output price |
| $0.54/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V4 Pro | Qwen2.5-72B-Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | Yes | No |
| JSON / 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 V4 Pro | Qwen2.5-72B-Instruct |
|---|---|---|
| Google-Proof Q&A | 90.1 | 38.4 |
| HumanEval | 76.8 | 86.6 |
| Chatbot Arena | 1456.0 | 1270.0 |
| Massive Multitask Language Understanding | 90.1 | 88.2 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has DeepSeek V4 Pro at 90.1 and Qwen2.5-72B-Instruct at 38.4, with DeepSeek V4 Pro ahead by 51.7 points; HumanEval has DeepSeek V4 Pro at 76.8 and Qwen2.5-72B-Instruct at 86.6, with Qwen2.5-72B-Instruct ahead by 9.8 points; Chatbot Arena has DeepSeek V4 Pro at 1456 and Qwen2.5-72B-Instruct at 1270, with DeepSeek V4 Pro ahead by 186 points. The largest visible gap is 186 points on Chatbot Arena, 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 reasoning mode: DeepSeek V4 Pro, JSON / Tool use: DeepSeek V4 Pro, and JSON / Tool use: DeepSeek V4 Pro. 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 V4 Pro lists tiered pricing: Off-peak is $0.66/1M input and $1.98/1M output; Peak is $1.32/1M input and $3.96/1M output, while Qwen2.5-72B-Instruct lists $0.18/1M input and $0.54/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Qwen2.5-72B-Instruct lower by about $0.18 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 6 providers versus 8, so concentration risk also matters.
Choose DeepSeek V4 Pro when reasoning depth and larger context windows are central to the workload. Choose Qwen2.5-72B-Instruct when provider fit, lower input-token cost, and broader provider choice 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 V4 Pro or Qwen2.5-72B-Instruct?
DeepSeek V4 Pro supports 1M tokens, while Qwen2.5-72B-Instruct supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, DeepSeek V4 Pro or Qwen2.5-72B-Instruct?
DeepSeek V4 Pro lists tiered pricing: Off-peak is $0.66/1M input and $1.98/1M output; Peak is $1.32/1M input and $3.96/1M output. Qwen2.5-72B-Instruct lists $0.18/1M input and $0.54/1M output tokens on the cheapest tracked provider. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V4 Pro or Qwen2.5-72B-Instruct open source?
DeepSeek V4 Pro is listed under MIT. Qwen2.5-72B-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 reasoning mode, DeepSeek V4 Pro or Qwen2.5-72B-Instruct?
DeepSeek V4 Pro has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for JSON / Tool use, DeepSeek V4 Pro or Qwen2.5-72B-Instruct?
DeepSeek V4 Pro has the clearer documented JSON / Tool use signal in this comparison. If JSON / 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 V4 Pro and Qwen2.5-72B-Instruct?
DeepSeek V4 Pro is available on DeepSeek Platform, Fireworks AI, OpenRouter, Vercel AI Gateway, and Novita AI. Qwen2.5-72B-Instruct is available on DeepInfra, OpenRouter, Fireworks AI, Novita AI, and Chutes AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-10-08. Data sourced from public model cards and provider documentation.