o3-mini vs Qwen3 Max vs DeepSeek-R1
Too close to call on our weighted score (o3-mini 52, DeepSeek-R1 51, Qwen3 Max 50). The right pick depends on what you value most.
OpenAIo3-mini
52/100- ECI140.3
- Price$1.10 / $4.40
- Context200K
Alibaba (Qwen)Qwen3 Max
50/100- ECI142.4
- Price$1.20 / $6.00
- Context262K
DeepSeekDeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
Too close to call
It is close. Our weighted score puts them within a point (o3-mini 52/100, DeepSeek-R1 51/100, Qwen3 Max 50/100), so choose by what matters most for your work: Qwen3 Max for raw capability and DeepSeek-R1 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 MaxCapabilities Index (ECI): Qwen3 Max 142.4 · o3-mini 140.3 · DeepSeek-R1 139.0
- Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · o3-mini $1.93 · Qwen3 Max $2.40 per 1M tokens (3:1 blend)
- Longest contextQwen3 MaxQwen3 Max 262,144 · o3-mini 200,000 · DeepSeek-R1 128,000 tokens
- Widest inputsSame inputso3-mini: Text · Qwen3 Max: Text · DeepSeek-R1: Text
- Self-hostingDeepSeek-R1Publishes downloadable weights
| Measure | Weight | o3-mini | Qwen3 Max | DeepSeek-R1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 66 | 68 | 64 |
| Price | 25% | 36 | 32 | 47 |
| Inputs & features | 15% | 45 | 25 | 35 |
| Context window | 10% | 32 | 37 | 24 |
| Overall | 100% | 52/100 | 50/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | o3-miniOpenAI | Qwen3 MaxAlibaba (Qwen) | DeepSeek-R1DeepSeek |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 140.3 | 142.4 (best) | 139.0 |
| ECI rank | #98 of 148 | #91 of 148 (best) | #104 of 148 |
| GPQA DiamondGraduate-level science questions | 77.0% (best) | 72.6% | 71.7% |
| FrontierMath Tiers 1–3Research-level mathematics | 18.6% | 19.0% (best) | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 76.9% (best) | 73.3% | 53.3% |
| SimpleQA VerifiedShort factual questions | 15.3% | 48.8% (best) | — |
| Price per million tokens | |||
| Input | $1.10 | $1.20 | $0.70 (best) |
| Output | $4.40 | $6.00 | $2.60 (best) |
| Cached input | $0.55 | — | — |
| Blended (3:1) | $1.93 | $2.40 | $1.18 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official Alibaba API | Median of 11 providers |
| Limits | |||
| Context window | 200,000 tokens | 262,144 tokens (best) | 128,000 tokens |
| Max output | 100,000 tokens (best) | 65,536 tokens | 32,768 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 | Yeslow · medium · high | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | o3-mini | qwen3-max | — |
| API providers | 15 | 16 (best) | 12 |
| Released | Jan 31, 2025 | Sep 23, 2025 | Jan 20, 2025 |
| Knowledge cutoff | May 2024 | Apr 2025 | Jul 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- o3-mini$19.80
- Qwen3 Max$24.00
- DeepSeek-R1$12.20
Which should you choose?
Which is better: o3-mini, Qwen3 Max or DeepSeek-R1?
It is close. Our weighted score puts them within a point (o3-mini 52/100, DeepSeek-R1 51/100, Qwen3 Max 50/100), so choose by what matters most for your work: Qwen3 Max for raw capability and DeepSeek-R1 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, o3-mini, Qwen3 Max or DeepSeek-R1?
DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 API providers). o3-mini costs $1.10 input / $4.40 output per million tokens (official OpenAI API price); Qwen3 Max costs $1.20 input / $6.00 output per million tokens (official Alibaba 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 $1.93 for o3-mini (1.6× as much) and $2.40 for Qwen3 Max (2× as much).
Which scores higher on benchmarks?
Qwen3 Max scores higher on the Capabilities Index (ECI): Qwen3 Max 142.4 (#91 of 148), o3-mini 140.3 (#98 of 148) and DeepSeek-R1 139.0 (#104 of 148). The confidence ranges of the top two overlap (140.0–144.6 vs 137.4–141.9), so treat the gap as small. On individual benchmarks: GPQA Diamond — o3-mini 77.0%, Qwen3 Max 72.6%, DeepSeek-R1 71.7%; OTIS Mock AIME 2024–2025 — o3-mini 76.9%, Qwen3 Max 73.3%, DeepSeek-R1 53.3%.
Which is better for coding?
There are no published SWE-bench Verified results for o3-mini, Qwen3 Max and DeepSeek-R1 yet, so there is no like-for-like coding score. On overall capability, Qwen3 Max 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?
Qwen3 Max has the largest context window at 262,144 tokens, against 200,000 for o3-mini and 128,000 for DeepSeek-R1. Maximum output per response: o3-mini up to 100,000, Qwen3 Max up to 65,536, DeepSeek-R1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
o3-mini accepts text; Qwen3 Max accepts text; DeepSeek-R1 accepts text. They handle the same number of input types.
Are any of these open source?
DeepSeek-R1 publishes its weights and can be self-hosted; o3-mini and Qwen3 Max is proprietary.
Which is newer?
Qwen3 Max is the newest, released Sep 23, 2025. o3-mini came out Jan 31, 2025; DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: o3-mini May 2024, Qwen3 Max Apr 2025, DeepSeek-R1 Jul 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.
