Qwen3 14B vs GPT-4.1 mini vs DeepSeek-V3.1
GPT-4.1 mini comes out ahead, 60 to 55 and 54 on our weighted score, though DeepSeek-V3.1 is 14% cheaper per token.
Alibaba (Qwen)Qwen3 14B
54/100- ECI138.2
- Price$0.35 / $1.40
- Context131K
- Our pick
OpenAIGPT-4.1 mini
60/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
DeepSeekDeepSeek-V3.1
55/100- ECI139.9
- Price$0.385 / $1.25
- Context131K
GPT-4.1 mini is our pick
GPT-4.1 mini is the better all-round choice, scoring 60/100 against DeepSeek-V3.1 (55) and Qwen3 14B (54). It leads on inputs & features and context window. DeepSeek-V3.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek-V3.1Capabilities Index (ECI): DeepSeek-V3.1 139.9 · Qwen3 14B 138.2 · GPT-4.1 mini 135.0
- Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · Qwen3 14B $0.613 · GPT-4.1 mini $0.70 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 miniGPT-4.1 mini 1,047,576 · Qwen3 14B 131,072 · DeepSeek-V3.1 131,072 tokens
- Widest inputsGPT-4.1 miniQwen3 14B: Text · GPT-4.1 mini: Text, Images, PDFs · DeepSeek-V3.1: Text
- Self-hostingQwen3 14B and DeepSeek-V3.1Publishes downloadable weights (MIT License)
| Measure | Weight | Qwen3 14B | GPT-4.1 mini | DeepSeek-V3.1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 63 | 59 | 65 |
| Price | 25% | 60 | 57 | 60 |
| Inputs & features | 15% | 35 | 70 | 35 |
| Context window | 10% | 24 | 61 | 24 |
| Overall | 100% | 54/100 | 60/100 | 55/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 14BAlibaba (Qwen) | GPT-4.1 miniOpenAI | DeepSeek-V3.1DeepSeek |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 138.2 | 135.0 | 139.9 (best) |
| ECI rank | #107 of 148 | #115 of 148 | #100 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 63.8% | 65.9% (best) | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 6.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 66.4% (best) | 44.7% | — |
| SimpleQA VerifiedShort factual questions | — | 12.7% | — |
| Price per million tokens | |||
| Input | $0.35 (best) | $0.40 | $0.385 |
| Output | $1.40 | $1.60 | $1.25 (best) |
| Cached input | — | $0.10 | — |
| Blended (3:1) | $0.613 | $0.70 | $0.601 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official OpenAI API | Median of 8 providers |
| Limits | |||
| Context window | 131,072 tokens | 1,047,576 tokens (best) | 131,072 tokens |
| Max output | 8,192 tokens | 32,768 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | OpenMIT License |
| API model ID | qwen3-14b | gpt-4.1-mini | — |
| API providers | 1 | 24 (best) | 8 |
| Released | Apr 29, 2025 | Apr 14, 2025 | Aug 21, 2025 |
| Knowledge cutoff | Apr 2025 | Apr 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3 14B$6.30
- GPT-4.1 mini$7.20
- DeepSeek-V3.1$6.35
Which should you choose?
Which is better: Qwen3 14B, GPT-4.1 mini or DeepSeek-V3.1?
GPT-4.1 mini is the better all-round choice, scoring 60/100 against DeepSeek-V3.1 (55) and Qwen3 14B (54). It leads on inputs & features and context window. DeepSeek-V3.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 14B, GPT-4.1 mini or DeepSeek-V3.1?
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); GPT-4.1 mini costs $0.40 input / $1.60 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 $0.70 for GPT-4.1 mini (1.2× as much).
Which scores higher on benchmarks?
DeepSeek-V3.1 scores higher on the Capabilities Index (ECI): DeepSeek-V3.1 139.9 (#100 of 148), Qwen3 14B 138.2 (#107 of 148) and GPT-4.1 mini 135.0 (#115 of 148). The confidence ranges of the top two overlap (136.1–143.3 vs 133.5–140.1), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 14B, GPT-4.1 mini and DeepSeek-V3.1 yet, so there is no like-for-like coding score. On overall capability, DeepSeek-V3.1 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?
GPT-4.1 mini has the largest context window at 1,047,576 tokens, against 131,072 for Qwen3 14B and 131,072 for DeepSeek-V3.1. Maximum output per response: Qwen3 14B up to 8,192, GPT-4.1 mini up to 32,768, DeepSeek-V3.1 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Qwen3 14B accepts text; GPT-4.1 mini accepts text, images and PDFs; DeepSeek-V3.1 accepts text. GPT-4.1 mini handles the widest range of inputs.
Are any of these open source?
Qwen3 14B and DeepSeek-V3.1 publishes its weights (MIT License) and can be self-hosted; GPT-4.1 mini is proprietary.
Which is newer?
DeepSeek-V3.1 is the newest, released Aug 21, 2025. Qwen3 14B came out Apr 29, 2025; GPT-4.1 mini came out Apr 14, 2025. Knowledge cutoff: Qwen3 14B Apr 2025, GPT-4.1 mini Apr 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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