Ministral 14B vs GPT-5.1 Codex mini vs Seed 2.0 Lite
Seed 2.0 Lite comes out ahead, 73 to 64 and 59 on our weighted score.
Mistral AIMinistral 14B
64/100- ECI—
- Price$0.20 / $0.20
- Context262K
OpenAIGPT-5.1 Codex mini
59/100- ECI—
- Price$0.25 / $2.00
- Context400K
- Our pick
ByteDance SeedSeed 2.0 Lite
73/100- ECI—
- Price$0.089 / $0.534
- Context256K
Seed 2.0 Lite is our pick
Seed 2.0 Lite is the better all-round choice, scoring 73/100 against Ministral 14B (64) and GPT-5.1 Codex mini (59). It leads on inputs & features. GPT-5.1 Codex mini wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. 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 priceMinistral 14BMinistral 14B $0.20 · Seed 2.0 Lite $0.20 · GPT-5.1 Codex mini $0.688 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 Codex miniGPT-5.1 Codex mini 400,000 · Ministral 14B 262,144 · Seed 2.0 Lite 256,000 tokens
- Widest inputsSeed 2.0 LiteMinistral 14B: Text, Images · GPT-5.1 Codex mini: Text, Images · Seed 2.0 Lite: Text, Images, Video
- Self-hostingMinistral 14BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Ministral 14B | GPT-5.1 Codex mini | Seed 2.0 Lite |
|---|---|---|---|---|
| Price | 50% | 83 | 58 | 83 |
| Inputs & features | 30% | 50 | 70 | 80 |
| Context window | 20% | 37 | 44 | 36 |
| Overall | 100% | 64/100 | 59/100 | 73/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Ministral 14BMistral AI | GPT-5.1 Codex miniOpenAI | Seed 2.0 LiteByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.20 | $0.25 | $0.089 (best) |
| Output | $0.20 (best) | $2.00 | $0.534 |
| Cached input | — | — | $0.018 |
| Blended (3:1) | $0.20 (best) | $0.688 | $0.20 |
| Long-context rate | Same rate | Same rate | Over 32K: $0.134 / $0.802 |
| Price source | Median of 1 providers | Median of 10 providers | Official Volcengine Ark API |
| Limits | |||
| Context window | 262,144 tokens | 400,000 tokens (best) | 256,000 tokens |
| Max output | 262,144 tokens (best) | 128,000 tokens | 32,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | No | Yes | Yesminimal · low · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenApache-2.0 | Proprietary | Proprietary |
| API model ID | — | — | doubao-seed-2-0-lite-260428 |
| API providers | 1 | 10 (best) | 6 |
| Released | Dec 2, 2025 | Nov 13, 2025 | Feb 14, 2026 |
| Knowledge cutoff | — | Sep 30, 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Ministral 14B$2.40
- GPT-5.1 Codex mini$6.50
- Seed 2.0 Lite$1.96
Which should you choose?
Which is better: Ministral 14B, GPT-5.1 Codex mini or Seed 2.0 Lite?
Seed 2.0 Lite is the better all-round choice, scoring 73/100 against Ministral 14B (64) and GPT-5.1 Codex mini (59). It leads on inputs & features. GPT-5.1 Codex mini wins on context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Ministral 14B, GPT-5.1 Codex mini or Seed 2.0 Lite?
Ministral 14B is cheaper at $0.20 input / $0.20 output per million tokens (median across 1 API provider). Seed 2.0 Lite costs $0.089 input / $0.534 output per million tokens (official Volcengine Ark API price); GPT-5.1 Codex mini costs $0.25 input / $2.00 output per million tokens (median across 10 API providers). At a typical mix of three input tokens to one output token, that is $0.20 per million tokens for Ministral 14B versus $0.20 for Seed 2.0 Lite (1× as much) and $0.688 for GPT-5.1 Codex mini (3.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Ministral 14B has not been scored yet, GPT-5.1 Codex mini has not been scored yet and Seed 2.0 Lite has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Ministral 14B, GPT-5.1 Codex mini and Seed 2.0 Lite yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-5.1 Codex mini has the largest context window at 400,000 tokens, against 262,144 for Ministral 14B and 256,000 for Seed 2.0 Lite. Maximum output per response: Ministral 14B up to 262,144, GPT-5.1 Codex mini up to 128,000, Seed 2.0 Lite up to 32,000 tokens.
Which can read images, PDFs, audio or video?
Ministral 14B accepts text and images; GPT-5.1 Codex mini accepts text and images; Seed 2.0 Lite accepts text, images and video. Seed 2.0 Lite handles the widest range of inputs.
Are any of these open source?
Ministral 14B publishes its weights (Apache-2.0) and can be self-hosted; GPT-5.1 Codex mini and Seed 2.0 Lite is proprietary.
Which is newer?
Seed 2.0 Lite is the newest, released Feb 14, 2026. Ministral 14B came out Dec 2, 2025; GPT-5.1 Codex mini came out Nov 13, 2025. Knowledge cutoff: GPT-5.1 Codex mini Sep 30, 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.
