o3-mini vs DeepSeek-R1
Too close to call on our weighted score (o3-mini 52, DeepSeek-R1 51). The right pick depends on what you value most.
OpenAIo3-mini
52/100- ECI140.3
- Price$1.10 / $4.40
- Context200K
DeepSeekDeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (o3-mini 52/100, DeepSeek-R1 51/100), so choose by what matters most for your work: o3-mini for raw capability and DeepSeek-R1 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- Capabilityo3-miniCapabilities Index (ECI): o3-mini 140.3 · DeepSeek-R1 139.0
- Lowest priceDeepSeek-R1DeepSeek-R1 $1.18 · o3-mini $1.93 per 1M tokens (3:1 blend)
- Longest contexto3-minio3-mini 200,000 · DeepSeek-R1 128,000 tokens
- Widest inputsSame inputso3-mini: Text · DeepSeek-R1: Text
- Self-hostingDeepSeek-R1Publishes downloadable weights
| Measure | Weight | o3-mini | DeepSeek-R1 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 66 | 64 |
| Price | 25% | 36 | 47 |
| Inputs & features | 15% | 45 | 35 |
| Context window | 10% | 32 | 24 |
| Overall | 100% | 52/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | o3-miniOpenAI | DeepSeek-R1DeepSeek |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 140.3 (best) | 139.0 |
| ECI rank | #98 of 148 (best) | #104 of 148 |
| GPQA DiamondGraduate-level science questions | 77.0% (best) | 71.7% |
| FrontierMath Tiers 1–3Research-level mathematics | 18.6% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 76.9% (best) | 53.3% |
| SimpleQA VerifiedShort factual questions | 15.3% | — |
| Price per million tokens | ||
| Input | $1.10 | $0.70 (best) |
| Output | $4.40 | $2.60 (best) |
| Cached input | $0.55 | — |
| Blended (3:1) | $1.93 | $1.18 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official OpenAI API | Median of 11 providers |
| Limits | ||
| Context window | 200,000 tokens (best) | 128,000 tokens |
| Max output | 100,000 tokens (best) | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | Open |
| API model ID | o3-mini | — |
| API providers | 15 (best) | 12 |
| Released | Jan 31, 2025 | Jan 20, 2025 |
| Knowledge cutoff | May 2024 | 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
- DeepSeek-R1$12.20
Which should you choose?
Which is better: o3-mini or DeepSeek-R1?
It is close. Our weighted score puts them within a point (o3-mini 52/100, DeepSeek-R1 51/100), so choose by what matters most for your work: o3-mini 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 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). 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).
Which scores higher on benchmarks?
o3-mini scores higher on the Capabilities Index (ECI): o3-mini 140.3 (#98 of 148) and DeepSeek-R1 139.0 (#104 of 148). The confidence ranges of the top two overlap (137.4–141.9 vs 136.2–140.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — o3-mini 77.0%, DeepSeek-R1 71.7%; OTIS Mock AIME 2024–2025 — o3-mini 76.9%, DeepSeek-R1 53.3%.
Which is better for coding?
There are no published SWE-bench Verified results for o3-mini and DeepSeek-R1 yet, so there is no like-for-like coding score. On overall capability, o3-mini leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
o3-mini has the largest context window at 200,000 tokens, against 128,000 for DeepSeek-R1. Maximum output per response: o3-mini up to 100,000, DeepSeek-R1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
o3-mini 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 is proprietary.
Which is newer?
o3-mini is the newest, released Jan 31, 2025. DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: o3-mini May 2024, 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.
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