DeepSeek-R1 vs QwQ 32B vs Qwen3 235B-A22B
Too close to call on our weighted score (QwQ 32B 53, Qwen3 235B-A22B 51, DeepSeek-R1 51). The right pick depends on what you value most.
DeepSeekDeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
Alibaba (Qwen)QwQ 32B
53/100- ECI137.6
- Price$0.66 / $1.00
- Context131K
- Alibaba (Qwen)
Qwen3 235B-A22B
51/100- ECI139.4
- Price$0.70 / $2.80
- Context131K
Too close to call
It is close. Our weighted score puts them within 1 points (QwQ 32B 53/100, Qwen3 235B-A22B 51/100, DeepSeek-R1 51/100), so choose by what matters most for your work: Qwen3 235B-A22B for raw capability and QwQ 32B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 235B-A22BCapabilities Index (ECI): Qwen3 235B-A22B 139.4 · DeepSeek-R1 139.0 · QwQ 32B 137.6
- Lowest priceQwQ 32BQwQ 32B $0.745 · DeepSeek-R1 $1.18 · Qwen3 235B-A22B $1.23 per 1M tokens (3:1 blend)
- Longest contextQwQ 32B and Qwen3 235B-A22BQwQ 32B 131,072 · Qwen3 235B-A22B 131,072 · DeepSeek-R1 128,000 tokens
- Widest inputsSame inputsDeepSeek-R1: Text · QwQ 32B: Text · Qwen3 235B-A22B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-R1 | QwQ 32B | Qwen3 235B-A22B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 62 | 65 |
| Price | 25% | 47 | 56 | 46 |
| Inputs & features | 15% | 35 | 35 | 35 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 51/100 | 53/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-R1DeepSeek | QwQ 32BAlibaba (Qwen) | Qwen3 235B-A22BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.0 | 137.6 | 139.4 (best) |
| ECI rank | #104 of 148 | #109 of 148 | #103 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 71.7% (best) | 65.3% | 70.7% |
| OTIS Mock AIME 2024–2025Competition mathematics | 53.3% | 59.2% (best) | — |
| Price per million tokens | |||
| Input | $0.70 | $0.66 (best) | $0.70 |
| Output | $2.60 | $1.00 (best) | $2.80 |
| Cached input | — | — | — |
| Blended (3:1) | $1.18 | $0.745 (best) | $1.23 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 1 providers | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Max output | 32,768 tokens (best) | 8,192 tokens | 16,384 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 | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | — | qwen3-235b-a22b |
| API providers | 12 (best) | 1 | 7 |
| Released | Jan 20, 2025 | Mar 5, 2025 | Apr 28, 2025 |
| Knowledge cutoff | Jul 2024 | Apr 2024 | Apr 2025 |
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$12.20
- QwQ 32B$8.60
- Qwen3 235B-A22B$12.60
Which should you choose?
Which is better: DeepSeek-R1, QwQ 32B or Qwen3 235B-A22B?
It is close. Our weighted score puts them within 1 points (QwQ 32B 53/100, Qwen3 235B-A22B 51/100, DeepSeek-R1 51/100), so choose by what matters most for your work: Qwen3 235B-A22B for raw capability and QwQ 32B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-R1, QwQ 32B or Qwen3 235B-A22B?
QwQ 32B is cheaper at $0.66 input / $1.00 output per million tokens (median across 1 API provider). DeepSeek-R1 costs $0.70 input / $2.60 output per million tokens (median across 11 API providers); Qwen3 235B-A22B costs $0.70 input / $2.80 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.745 per million tokens for QwQ 32B versus $1.18 for DeepSeek-R1 (1.6× as much) and $1.23 for Qwen3 235B-A22B (1.6× as much).
Which scores higher on benchmarks?
Qwen3 235B-A22B scores higher on the Capabilities Index (ECI): Qwen3 235B-A22B 139.4 (#103 of 148), DeepSeek-R1 139.0 (#104 of 148) and QwQ 32B 137.6 (#109 of 148). The confidence ranges of the top two overlap (135.2–140.8 vs 136.2–140.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-R1 71.7%, Qwen3 235B-A22B 70.7%, QwQ 32B 65.3%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1, QwQ 32B and Qwen3 235B-A22B yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
QwQ 32B and Qwen3 235B-A22B have the largest context windows (131,072 and 131,072 tokens), against 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, QwQ 32B up to 8,192, Qwen3 235B-A22B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1 accepts text; QwQ 32B accepts text; Qwen3 235B-A22B 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?
Qwen3 235B-A22B is the newest, released Apr 28, 2025. QwQ 32B came out Mar 5, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, QwQ 32B Apr 2024, Qwen3 235B-A22B Apr 2025.
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.
