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. On pricing, Qwen2.5-72B-Instruct costs $0.18/1M input tokens versus $0.43/1M 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.
Qwen2.5-72B-Instruct is ~142% cheaper at $0.18/1M; pay for DeepSeek V4 Pro only for reasoning depth.
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 | $0.87/1M tokens | $0.54/1M tokens |
| Provider routes | 5 tracked | 7 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
$566
Cheapest tracked route/tier: DeepSeek Platform
Qwen2.5-72B-Instruct
$279
Cheapest tracked route/tier: Chutes AI
Estimated monthly gap: $287. 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 $0.33/1M 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 $0.33/1M 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 | Commercial use: permitted | Commercial use: permitted |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | DeepSeek V4 Pro | Qwen2.5-72B-Instruct |
|---|---|---|
| Input price | $0.43/1M tokens | $0.18/1M tokens |
| Output price | $0.87/1M tokens | $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 |
Continue comparing
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Last reviewed: 2026-06-30. Data sourced from public model cards and provider documentation.