DeepSeek-R1 vs DeepSeek V4 Pro vs Qwen3 235B-A22B
DeepSeek V4 Pro comes out ahead, 45 to 39 and 38 on our weighted score, though DeepSeek-R1 is 32% cheaper per token.
DeepSeekDeepSeek-R1
39/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
- Our pickDeepSeek
DeepSeek V4 Pro
45/100- ECI—
- Price$1.32 / $3.00
- Context1M
Alibaba (Qwen)Qwen3 235B-A22B
38/100- ECI139.4
- Price$0.70 / $2.80
- Context131K
DeepSeek V4 Pro is our pick
DeepSeek V4 Pro is the better all-round choice, scoring 45/100 against DeepSeek-R1 (39) and Qwen3 235B-A22B (38). It leads on inputs & features and context window. 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 priceDeepSeek-R1DeepSeek-R1 $1.18 · Qwen3 235B-A22B $1.23 · DeepSeek V4 Pro $1.74 per 1M tokens (3:1 blend)
- Longest contextDeepSeek V4 ProDeepSeek V4 Pro 1,000,000 · Qwen3 235B-A22B 131,072 · DeepSeek-R1 128,000 tokens
- Widest inputsSame inputsDeepSeek-R1: Text · DeepSeek V4 Pro: Text · Qwen3 235B-A22B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-R1 | DeepSeek V4 Pro | Qwen3 235B-A22B |
|---|---|---|---|---|
| Price | 50% | 47 | 38 | 46 |
| Inputs & features | 30% | 35 | 45 | 35 |
| Context window | 20% | 24 | 60 | 24 |
| Overall | 100% | 39/100 | 45/100 | 38/100 |
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-R1DeepSeek | DeepSeek V4 ProDeepSeek | Qwen3 235B-A22BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.0 | — | 139.4 (best) |
| ECI rank | #104 of 148 | — | #103 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 71.7% (best) | — | 70.7% |
| OTIS Mock AIME 2024–2025Competition mathematics | 53.3% | — | — |
| Price per million tokens | |||
| Input | $0.70 (best) | $1.32 | $0.70 (best) |
| Output | $2.60 (best) | $3.00 | $2.80 |
| Cached input | — | — | — |
| Blended (3:1) | $1.18 (best) | $1.74 | $1.23 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 49 providers | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens | 1,000,000 tokens (best) | 131,072 tokens |
| Max output | 32,768 tokens | 384,000 tokens (best) | 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 | Yes | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | — | qwen3-235b-a22b |
| API providers | 12 | 52 (best) | 7 |
| Released | Jan 20, 2025 | Apr 24, 2026 | Apr 28, 2025 |
| Knowledge cutoff | Jul 2024 | May 2025 | 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
- DeepSeek V4 Pro$19.20
- Qwen3 235B-A22B$12.60
Which should you choose?
Which is better: DeepSeek-R1, DeepSeek V4 Pro or Qwen3 235B-A22B?
DeepSeek V4 Pro is the better all-round choice, scoring 45/100 against DeepSeek-R1 (39) and Qwen3 235B-A22B (38). It leads on inputs & features and context window. 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-R1, DeepSeek V4 Pro or Qwen3 235B-A22B?
DeepSeek-R1 is cheaper at $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); 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 $1.18 per million tokens for DeepSeek-R1 versus $1.23 for Qwen3 235B-A22B (1× as much) and $1.74 for DeepSeek V4 Pro (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DeepSeek-R1 has an ECI of 139.0, DeepSeek V4 Pro has not been scored yet and Qwen3 235B-A22B has an ECI of 139.4.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1, DeepSeek V4 Pro and Qwen3 235B-A22B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three 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 Qwen3 235B-A22B and 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, DeepSeek V4 Pro up to 384,000, Qwen3 235B-A22B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1 accepts text; DeepSeek V4 Pro 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?
DeepSeek V4 Pro is the newest, released Apr 24, 2026. Qwen3 235B-A22B came out Apr 28, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, DeepSeek V4 Pro May 2025, 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.
