DeepSeek-R1 vs DeepSeek V3 0324
Too close to call on our weighted score (DeepSeek V3 0324 54, DeepSeek-R1 51). The right pick depends on what you value most.
DeepSeekDeepSeek-R1
51/100- ECI139.0
- Price$0.70 / $2.60
- Context128K
- DeepSeek
DeepSeek V3 0324
54/100- ECI135.9
- Price$0.24 / $0.90
- Context164K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 3 points (DeepSeek V3 0324 54/100, DeepSeek-R1 51/100), so choose by what matters most for your work: DeepSeek-R1 for raw capability, DeepSeek V3 0324 on price and DeepSeek V3 0324 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek-R1Capabilities Index (ECI): DeepSeek-R1 139.0 · DeepSeek V3 0324 135.9
- Lowest priceDeepSeek V3 0324DeepSeek V3 0324 $0.405 · DeepSeek-R1 $1.18 per 1M tokens (3:1 blend)
- Longest contextDeepSeek V3 0324DeepSeek V3 0324 163,840 · DeepSeek-R1 128,000 tokens
- Widest inputsSame inputsDeepSeek-R1: Text · DeepSeek V3 0324: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek-R1 | DeepSeek V3 0324 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 60 |
| Price | 25% | 47 | 68 |
| Inputs & features | 15% | 35 | 25 |
| Context window | 10% | 24 | 28 |
| Overall | 100% | 51/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-R1DeepSeek | DeepSeek V3 0324DeepSeek |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 139.0 (best) | 135.9 |
| ECI rank | #104 of 148 (best) | #114 of 148 |
| GPQA DiamondGraduate-level science questions | 71.7% (best) | 67.6% |
| OTIS Mock AIME 2024–2025Competition mathematics | 53.3% (best) | 37.8% |
| Price per million tokens | ||
| Input | $0.70 | $0.24 (best) |
| Output | $2.60 | $0.90 (best) |
| Cached input | — | — |
| Blended (3:1) | $1.18 | $0.405 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 5 providers |
| Limits | ||
| Context window | 128,000 tokens | 163,840 tokens (best) |
| Max output | 32,768 tokens | 163,840 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | — | — |
| API providers | 12 (best) | 5 |
| Released | Jan 20, 2025 | Mar 24, 2025 |
| Knowledge cutoff | 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.
- DeepSeek-R1$12.20
- DeepSeek V3 0324$4.20
Which should you choose?
Which is better: DeepSeek-R1 or DeepSeek V3 0324?
It is close. Our weighted score puts them within 3 points (DeepSeek V3 0324 54/100, DeepSeek-R1 51/100), so choose by what matters most for your work: DeepSeek-R1 for raw capability, DeepSeek V3 0324 on price and DeepSeek V3 0324 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-R1 or DeepSeek V3 0324?
DeepSeek V3 0324 is cheaper at $0.24 input / $0.90 output per million tokens (median across 5 API providers). DeepSeek-R1 costs $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 $0.405 per million tokens for DeepSeek V3 0324 versus $1.18 for DeepSeek-R1 (2.9× as much).
Which scores higher on benchmarks?
DeepSeek-R1 scores higher on the Capabilities Index (ECI): DeepSeek-R1 139.0 (#104 of 148) and DeepSeek V3 0324 135.9 (#114 of 148). The confidence ranges of the top two overlap (136.2–140.4 vs 132.4–138.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-R1 71.7%, DeepSeek V3 0324 67.6%; OTIS Mock AIME 2024–2025 — DeepSeek-R1 53.3%, DeepSeek V3 0324 37.8%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-R1 and DeepSeek V3 0324 yet, so there is no like-for-like coding score. On overall capability, DeepSeek-R1 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?
DeepSeek V3 0324 has the largest context window at 163,840 tokens, against 128,000 for DeepSeek-R1. Maximum output per response: DeepSeek-R1 up to 32,768, DeepSeek V3 0324 up to 163,840 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-R1 accepts text; DeepSeek V3 0324 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
DeepSeek V3 0324 is the newest, released Mar 24, 2025. DeepSeek-R1 came out Jan 20, 2025. Knowledge cutoff: 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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