DeepSeek-R1-Distill-Qwen-32B vs DeepSeek V4 Pro vs QwQ 32B
DeepSeek V4 Pro comes out ahead, 51 to 31 and 16 on our weighted score, though QwQ 32B is 2.3× cheaper per token.
DeepSeekDeepSeek-R1-Distill-Qwen-32B
16/100- ECI137.4
- Price—
- Context131K
- Our pickDeepSeek
DeepSeek V4 Pro
51/100- ECI—
- Price$1.32 / $3.00
- Context1M
Alibaba (Qwen)QwQ 32B
31/100- ECI137.6
- Price$0.66 / $1.00
- Context131K
DeepSeek V4 Pro is our pick
DeepSeek V4 Pro is the better all-round choice, scoring 51/100 against QwQ 32B (31) and DeepSeek-R1-Distill-Qwen-32B (16). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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) · DeepSeek-R1-Distill-Qwen-32B unpriced
- Longest contextDeepSeek V4 ProDeepSeek V4 Pro 1,000,000 · DeepSeek-R1-Distill-Qwen-32B 131,072 · QwQ 32B 131,072 tokens
- Widest inputsSame inputsDeepSeek-R1-Distill-Qwen-32B: Text · DeepSeek V4 Pro: Text · QwQ 32B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-R1-Distill-Qwen-32B | DeepSeek V4 Pro | QwQ 32B |
|---|---|---|---|---|
| Inputs & features | 60% | 10 | 45 | 35 |
| Context window | 40% | 24 | 60 | 24 |
| Overall | 100% | 16/100 | 51/100 | 31/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-R1-Distill-Qwen-32BDeepSeek | DeepSeek V4 ProDeepSeek | QwQ 32BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 137.4 | — | 137.6 (best) |
| ECI rank | #110 of 148 | — | #109 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 64.1% | — | 65.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 55.6% | — | 59.2% (best) |
| 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 | 131,072 tokens | 1,000,000 tokens (best) | 131,072 tokens |
| Max output | 32,768 tokens | 384,000 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | — | — |
| API providers | — | 52 (best) | 1 |
| Released | Jan 20, 2025 | 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-R1-Distill-Qwen-32B—
- DeepSeek V4 Pro$19.20
- QwQ 32B$8.60
Which should you choose?
Which is better: DeepSeek-R1-Distill-Qwen-32B, DeepSeek V4 Pro or QwQ 32B?
DeepSeek V4 Pro is the better all-round choice, scoring 51/100 against QwQ 32B (31) and DeepSeek-R1-Distill-Qwen-32B (16). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, DeepSeek-R1-Distill-Qwen-32B, 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). DeepSeek-R1-Distill-Qwen-32B has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DeepSeek-R1-Distill-Qwen-32B has an ECI of 137.4, 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-R1-Distill-Qwen-32B, 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. Note that DeepSeek-R1-Distill-Qwen-32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
DeepSeek V4 Pro has the largest context window at 1,000,000 tokens, against 131,072 for DeepSeek-R1-Distill-Qwen-32B and 131,072 for QwQ 32B. Maximum output per response: DeepSeek-R1-Distill-Qwen-32B up to 32,768, DeepSeek V4 Pro up to 384,000, QwQ 32B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1-Distill-Qwen-32B accepts text; DeepSeek V4 Pro accepts text; QwQ 32B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three 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; DeepSeek-R1-Distill-Qwen-32B came out Jan 20, 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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