DeepSeek-V3.1 vs o3-mini vs Qwen3 14B
Too close to call on our weighted score (DeepSeek-V3.1 55, Qwen3 14B 54, o3-mini 52). The right pick depends on what you value most.
DeepSeekDeepSeek-V3.1
55/100- ECI139.9
- Price$0.385 / $1.25
- Context131K
OpenAIo3-mini
52/100- ECI140.3
- Price$1.10 / $4.40
- Context200K
Alibaba (Qwen)Qwen3 14B
54/100- ECI138.2
- Price$0.35 / $1.40
- Context131K
Too close to call
It is close. Our weighted score puts them within 1 points (DeepSeek-V3.1 55/100, Qwen3 14B 54/100, o3-mini 52/100), so choose by what matters most for your work: o3-mini for raw capability and DeepSeek-V3.1 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- Capabilityo3-miniCapabilities Index (ECI): o3-mini 140.3 · DeepSeek-V3.1 139.9 · Qwen3 14B 138.2
- Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · Qwen3 14B $0.613 · o3-mini $1.93 per 1M tokens (3:1 blend)
- Longest contexto3-minio3-mini 200,000 · DeepSeek-V3.1 131,072 · Qwen3 14B 131,072 tokens
- Widest inputsSame inputsDeepSeek-V3.1: Text · o3-mini: Text · Qwen3 14B: Text
- Self-hostingDeepSeek-V3.1 and Qwen3 14BPublishes downloadable weights (MIT License)
| Measure | Weight | DeepSeek-V3.1 | o3-mini | Qwen3 14B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 65 | 66 | 63 |
| Price | 25% | 60 | 36 | 60 |
| Inputs & features | 15% | 35 | 45 | 35 |
| Context window | 10% | 24 | 32 | 24 |
| Overall | 100% | 55/100 | 52/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek-V3.1DeepSeek | o3-miniOpenAI | Qwen3 14BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.9 | 140.3 (best) | 138.2 |
| ECI rank | #100 of 148 | #98 of 148 (best) | #107 of 148 |
| GPQA DiamondGraduate-level science questions | — | 77.0% (best) | 63.8% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 18.6% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 76.9% (best) | 66.4% |
| SimpleQA VerifiedShort factual questions | — | 15.3% | — |
| Price per million tokens | |||
| Input | $0.385 | $1.10 | $0.35 (best) |
| Output | $1.25 (best) | $4.40 | $1.40 |
| Cached input | — | $0.55 | — |
| Blended (3:1) | $0.601 (best) | $1.93 | $0.613 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 8 providers | Official OpenAI API | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens (best) | 131,072 tokens |
| Max output | 8,192 tokens | 100,000 tokens (best) | 8,192 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 | Yes | Yeslow · medium · high | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenMIT License | Proprietary | Open |
| API model ID | — | o3-mini | qwen3-14b |
| API providers | 8 | 15 (best) | 1 |
| Released | Aug 21, 2025 | Jan 31, 2025 | Apr 29, 2025 |
| Knowledge cutoff | — | 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-V3.1$6.35
- o3-mini$19.80
- Qwen3 14B$6.30
Which should you choose?
Which is better: DeepSeek-V3.1, o3-mini or Qwen3 14B?
It is close. Our weighted score puts them within 1 points (DeepSeek-V3.1 55/100, Qwen3 14B 54/100, o3-mini 52/100), so choose by what matters most for your work: o3-mini for raw capability and DeepSeek-V3.1 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-V3.1, o3-mini or Qwen3 14B?
DeepSeek-V3.1 is cheaper at $0.385 input / $1.25 output per million tokens (median across 8 API providers). Qwen3 14B costs $0.35 input / $1.40 output per million tokens (official Alibaba API price); 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 $0.601 per million tokens for DeepSeek-V3.1 versus $0.613 for Qwen3 14B (1× as much) and $1.93 for o3-mini (3.2× as much).
Which scores higher on benchmarks?
o3-mini scores higher on the Capabilities Index (ECI): o3-mini 140.3 (#98 of 148), DeepSeek-V3.1 139.9 (#100 of 148) and Qwen3 14B 138.2 (#107 of 148). The confidence ranges of the top two overlap (137.4–141.9 vs 136.1–143.3), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek-V3.1, o3-mini and Qwen3 14B 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. All three support tool calling for agent workflows.
Which has the bigger context window?
o3-mini has the largest context window at 200,000 tokens, against 131,072 for DeepSeek-V3.1 and 131,072 for Qwen3 14B. Maximum output per response: DeepSeek-V3.1 up to 8,192, o3-mini up to 100,000, Qwen3 14B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-V3.1 accepts text; o3-mini accepts text; Qwen3 14B accepts text. They handle the same number of input types.
Are any of these open source?
DeepSeek-V3.1 and Qwen3 14B publishes its weights (MIT License) and can be self-hosted; o3-mini is proprietary.
Which is newer?
DeepSeek-V3.1 is the newest, released Aug 21, 2025. Qwen3 14B came out Apr 29, 2025; o3-mini came out Jan 31, 2025. Knowledge cutoff: o3-mini May 2024, Qwen3 14B 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.
