DeepSeek-R1 vs o4-mini vs Qwen3 235B-A22B
o4-mini comes out ahead, 59 to 51 and 51 on our weighted score, though DeepSeek-R1 is 39% cheaper per token.
DeepSeekDeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
- Our pick
OpenAIo4-mini
59/100- ECI145.6
- Price$1.10 / $4.40
- Context200K
Alibaba (Qwen)Qwen3 235B-A22B
51/100- ECI139.4
- Price$0.70 / $2.80
- Context131K
o4-mini is our pick
o4-mini is the better all-round choice, scoring 59/100 against Qwen3 235B-A22B (51) and DeepSeek-R1 (51). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- Capabilityo4-miniCapabilities Index (ECI): o4-mini 145.6 · Qwen3 235B-A22B 139.4 · DeepSeek-R1 139.0
- Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · Qwen3 235B-A22B $1.23 · o4-mini $1.93 per 1M tokens (3:1 blend)
- Longest contexto4-minio4-mini 200,000 · Qwen3 235B-A22B 131,072 · DeepSeek-R1 128,000 tokens
- Widest inputso4-miniDeepSeek-R1: Text · o4-mini: Text, Images · Qwen3 235B-A22B: Text
- Self-hostingDeepSeek-R1 and Qwen3 235B-A22BPublishes downloadable weights
| Measure | Weight | DeepSeek-R1 | o4-mini | Qwen3 235B-A22B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 73 | 65 |
| Price | 25% | 47 | 36 | 46 |
| Inputs & features | 15% | 35 | 70 | 35 |
| Context window | 10% | 24 | 32 | 24 |
| Overall | 100% | 51/100 | 59/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-R1DeepSeek | o4-miniOpenAI | Qwen3 235B-A22BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.0 | 145.6 (best) | 139.4 |
| ECI rank | #104 of 148 | #76 of 148 (best) | #103 of 148 |
| GPQA DiamondGraduate-level science questions | 71.7% | 79.6% (best) | 70.7% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 36.1% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 53.3% | 81.7% (best) | — |
| SimpleQA VerifiedShort factual questions | — | 19.6% | — |
| Price per million tokens | |||
| Input | $0.70 (best) | $1.10 | $0.70 (best) |
| Output | $2.60 (best) | $4.40 | $2.80 |
| Cached input | — | $0.275 | — |
| Blended (3:1) | $1.18 (best) | $1.93 | $1.23 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Official OpenAI API | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens | 200,000 tokens (best) | 131,072 tokens |
| Max output | 32,768 tokens | 100,000 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | — | o4-mini | qwen3-235b-a22b |
| API providers | 12 | 19 (best) | 7 |
| Released | Jan 20, 2025 | Apr 16, 2025 | Apr 28, 2025 |
| Knowledge cutoff | Jul 2024 | May 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
- o4-mini$19.80
- Qwen3 235B-A22B$12.60
Which should you choose?
Which is better: DeepSeek-R1, o4-mini or Qwen3 235B-A22B?
o4-mini is the better all-round choice, scoring 59/100 against Qwen3 235B-A22B (51) and DeepSeek-R1 (51). It leads on capability, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-R1, o4-mini 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); o4-mini costs $1.10 input / $4.40 output per million tokens (official OpenAI API price). 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 $1.93 for o4-mini (1.6× as much).
Which scores higher on benchmarks?
o4-mini scores higher on the Capabilities Index (ECI): o4-mini 145.6 (#76 of 148), Qwen3 235B-A22B 139.4 (#103 of 148) and DeepSeek-R1 139.0 (#104 of 148). Their confidence ranges do not overlap (143.0–147.4 vs 135.2–140.8), so the gap is a real one. On individual benchmarks: GPQA Diamond — o4-mini 79.6%, DeepSeek-R1 71.7%, Qwen3 235B-A22B 70.7%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1, o4-mini and Qwen3 235B-A22B yet, so there is no like-for-like coding score. On overall capability, o4-mini 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?
o4-mini has the largest context window at 200,000 tokens, against 131,072 for Qwen3 235B-A22B and 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, o4-mini up to 100,000, Qwen3 235B-A22B up to 16,384 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1 accepts text; o4-mini accepts text and images; Qwen3 235B-A22B accepts text. o4-mini handles the widest range of inputs.
Are any of these open source?
DeepSeek-R1 and Qwen3 235B-A22B publishes its weights and can be self-hosted; o4-mini is proprietary.
Which is newer?
Qwen3 235B-A22B is the newest, released Apr 28, 2025. o4-mini came out Apr 16, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: DeepSeek-R1 Jul 2024, o4-mini May 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.
