DeepSeek V4 Pro vs QwQ 32B
Too close to call on our weighted score (DeepSeek V4 Pro 45, QwQ 32B 43). The right pick depends on what you value most.
DeepSeekDeepSeek V4 Pro
45/100- ECI—
- Price$1.32 / $3.00
- Context1M
Alibaba (Qwen)QwQ 32B
43/100- ECI137.6
- Price$0.66 / $1.00
- Context131K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 1 points (DeepSeek V4 Pro 45/100, QwQ 32B 43/100), so choose by what matters most for your work: QwQ 32B on price and DeepSeek V4 Pro for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwQ 32BQwQ 32B $0.745 · DeepSeek V4 Pro $1.74 per 1M tokens (3:1 blend)
- Longest contextDeepSeek V4 ProDeepSeek V4 Pro 1,000,000 · QwQ 32B 131,072 tokens
- Widest inputsSame inputsDeepSeek V4 Pro: Text · QwQ 32B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek V4 Pro | QwQ 32B |
|---|---|---|---|
| Price | 50% | 38 | 56 |
| Inputs & features | 30% | 45 | 35 |
| Context window | 20% | 60 | 24 |
| Overall | 100% | 45/100 | 43/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek V4 ProDeepSeek | QwQ 32BAlibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 137.6 |
| ECI rank | — | #109 of 148 |
| GPQA DiamondGraduate-level science questions | — | 65.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 59.2% |
| Price per million tokens | ||
| Input | $1.32 | $0.66 (best) |
| Output | $3.00 | $1.00 (best) |
| Cached input | — | — |
| Blended (3:1) | $1.74 | $0.745 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 49 providers | Median of 1 providers |
| Limits | ||
| Context window | 1,000,000 tokens (best) | 131,072 tokens |
| Max output | 384,000 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | — | — |
| API providers | 52 (best) | 1 |
| Released | Apr 24, 2026 | Mar 5, 2025 |
| Knowledge cutoff | May 2025 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek V4 Pro$19.20
- QwQ 32B$8.60
Which should you choose?
Which is better: DeepSeek V4 Pro or QwQ 32B?
It is close. Our weighted score puts them within 1 points (DeepSeek V4 Pro 45/100, QwQ 32B 43/100), so choose by what matters most for your work: QwQ 32B on price and DeepSeek V4 Pro for long inputs. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, DeepSeek V4 Pro or QwQ 32B?
QwQ 32B is cheaper at $0.66 input / $1.00 output per million tokens (median across 1 API provider). DeepSeek V4 Pro costs $1.32 input / $3.00 output per million tokens (median across 49 API providers). At a typical mix of three input tokens to one output token, that is $0.745 per million tokens for QwQ 32B versus $1.74 for DeepSeek V4 Pro (2.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. DeepSeek V4 Pro has not been scored yet and QwQ 32B has an ECI of 137.6.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4 Pro and QwQ 32B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
DeepSeek V4 Pro has the largest context window at 1,000,000 tokens, against 131,072 for QwQ 32B. Maximum output per response: DeepSeek V4 Pro up to 384,000, QwQ 32B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4 Pro accepts text; QwQ 32B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
DeepSeek V4 Pro is the newest, released Apr 24, 2026. QwQ 32B came out Mar 5, 2025. Knowledge cutoff: DeepSeek V4 Pro May 2025, QwQ 32B Apr 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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