DeepSeek-R1 vs o4-mini-deep-research
o4-mini-deep-research comes out ahead, 49 to 31 on our weighted score.
DeepSeekDeepSeek-R1
31/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
- Our pick
OpenAIo4-mini-deep-research
49/100- ECI—
- Price—
- Context200K
Add a model
Make it a three-way comparison.
o4-mini-deep-research is our pick
o4-mini-deep-research is the better all-round choice, scoring 49/100 against DeepSeek-R1 (31). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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 per 1M tokens (3:1 blend) · o4-mini-deep-research unpriced
- Longest contexto4-mini-deep-researcho4-mini-deep-research 200,000 · DeepSeek-R1 128,000 tokens
- Widest inputso4-mini-deep-researchDeepSeek-R1: Text · o4-mini-deep-research: Text, Images
- Self-hostingDeepSeek-R1Publishes downloadable weights
| Measure | Weight | DeepSeek-R1 | o4-mini-deep-research |
|---|---|---|---|
| Inputs & features | 60% | 35 | 60 |
| Context window | 40% | 24 | 32 |
| Overall | 100% | 31/100 | 49/100 |
Left out because at least one model lacks the data: capability and price. 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 | o4-mini-deep-researchOpenAI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 139.0 | — |
| ECI rank | #104 of 148 | — |
| GPQA DiamondGraduate-level science questions | 71.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 53.3% | — |
| Price per million tokens | ||
| Input | $0.70 | — |
| Output | $2.60 | — |
| Cached input | — | — |
| Blended (3:1) | $1.18 | — |
| Long-context rate | Same rate | — |
| Price source | Median of 11 providers | — |
| Limits | ||
| Context window | 128,000 tokens | 200,000 tokens (best) |
| Max output | 32,768 tokens | 100,000 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | — | — |
| API providers | 12 | — |
| Released | Jan 20, 2025 | Jun 26, 2024 |
| Knowledge cutoff | Jul 2024 | May 2024 |
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-deep-research—
Which should you choose?
Which is better: DeepSeek-R1 or o4-mini-deep-research?
o4-mini-deep-research is the better all-round choice, scoring 49/100 against DeepSeek-R1 (31). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, DeepSeek-R1 or o4-mini-deep-research?
DeepSeek-R1 is cheaper at $0.70 input / $2.60 output per million tokens (median across 11 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 . o4-mini-deep-research has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. DeepSeek-R1 has an ECI of 139.0 and o4-mini-deep-research has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1 and o4-mini-deep-research yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
o4-mini-deep-research has the largest context window at 200,000 tokens, against 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, o4-mini-deep-research up to 100,000 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1 accepts text; o4-mini-deep-research accepts text and images. o4-mini-deep-research handles the widest range of inputs.
Are any of these open source?
DeepSeek-R1 publishes its weights and can be self-hosted; o4-mini-deep-research is proprietary.
Which is newer?
DeepSeek-R1 is the newest, released Jan 20, 2025. o4-mini-deep-research came out Jun 26, 2024. Knowledge cutoff: DeepSeek-R1 Jul 2024, o4-mini-deep-research May 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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