Trinity Nano Preview vs Gemini 2.5 Computer Use Preview vs Ministral 14B
Too close to call on our weighted score (Gemini 2.5 Computer Use Preview 46, Ministral 14B 45, Trinity Nano Preview 25). The right pick depends on what you value most.
Arcee AITrinity Nano Preview
25/100- ECI—
- Price—
- Context131K
GoogleGemini 2.5 Computer Use Preview
46/100- ECI—
- Price$1.25 / $10.00
- Context128K
Mistral AIMinistral 14B
45/100- ECI—
- Price$0.20 / $0.20
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (Gemini 2.5 Computer Use Preview 46/100, Ministral 14B 45/100, Trinity Nano Preview 25/100), so choose by what matters most for your work: Ministral 14B on price and Ministral 14B for long inputs. 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 priceMinistral 14BMinistral 14B $0.20 · Gemini 2.5 Computer Use Preview $3.44 per 1M tokens (3:1 blend) · Trinity Nano Preview unpriced
- Longest contextMinistral 14BMinistral 14B 262,144 · Trinity Nano Preview 131,072 · Gemini 2.5 Computer Use Preview 128,000 tokens
- Widest inputsGemini 2.5 Computer Use Preview and Ministral 14BTrinity Nano Preview: Text · Gemini 2.5 Computer Use Preview: Text, Images · Ministral 14B: Text, Images
- Self-hostingTrinity Nano Preview and Ministral 14BPublishes downloadable weights (OpenMDW-1.1 and Apache-2.0)
| Measure | Weight | Trinity Nano Preview | Gemini 2.5 Computer Use Preview | Ministral 14B |
|---|---|---|---|---|
| Inputs & features | 60% | 25 | 60 | 50 |
| Context window | 40% | 24 | 24 | 37 |
| Overall | 100% | 25/100 | 46/100 | 45/100 |
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 | Trinity Nano PreviewArcee AI | Gemini 2.5 Computer Use PreviewGoogle | Ministral 14BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $1.25 | $0.20 (best) |
| Output | — | $10.00 | $0.20 (best) |
| Cached input | — | — | — |
| Blended (3:1) | — | $3.44 | $0.20 (best) |
| Long-context rate | — | Over 200K: $2.50 / $15.00 | Same rate |
| Price source | — | Official Google API | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens | 128,000 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens | 64,000 tokens | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenOpenMDW-1.1 | Proprietary | OpenApache-2.0 |
| API model ID | — | gemini-2.5-computer-use-preview-10-2025 | — |
| API providers | — | 2 (best) | 1 |
| Released | Dec 1, 2025 | Oct 7, 2025 | Dec 2, 2025 |
| Knowledge cutoff | — | Jan 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Trinity Nano Preview—
- Gemini 2.5 Computer Use Preview$32.50
- Ministral 14B$2.40
Which should you choose?
Which is better: Trinity Nano Preview, Gemini 2.5 Computer Use Preview or Ministral 14B?
It is close. Our weighted score puts them within a point (Gemini 2.5 Computer Use Preview 46/100, Ministral 14B 45/100, Trinity Nano Preview 25/100), so choose by what matters most for your work: Ministral 14B on price and Ministral 14B for long inputs. 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, Trinity Nano Preview, Gemini 2.5 Computer Use Preview or Ministral 14B?
Ministral 14B is cheaper at $0.20 input / $0.20 output per million tokens (median across 1 API provider). Gemini 2.5 Computer Use Preview costs $1.25 input / $10.00 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $0.20 per million tokens for Ministral 14B versus $3.44 for Gemini 2.5 Computer Use Preview (17× as much). Trinity Nano Preview has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Trinity Nano Preview has not been scored yet, Gemini 2.5 Computer Use Preview has not been scored yet and Ministral 14B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Trinity Nano Preview, Gemini 2.5 Computer Use Preview and Ministral 14B 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?
Ministral 14B has the largest context window at 262,144 tokens, against 131,072 for Trinity Nano Preview and 128,000 for Gemini 2.5 Computer Use Preview. Maximum output per response: Trinity Nano Preview up to 131,072, Gemini 2.5 Computer Use Preview up to 64,000, Ministral 14B up to 262,144 tokens.
Which can read images, PDFs, audio or video?
Trinity Nano Preview accepts text; Gemini 2.5 Computer Use Preview accepts text and images; Ministral 14B accepts text and images. Gemini 2.5 Computer Use Preview handles the widest range of inputs.
Are any of these open source?
Trinity Nano Preview and Ministral 14B publishes its weights (OpenMDW-1.1 and Apache-2.0) and can be self-hosted; Gemini 2.5 Computer Use Preview is proprietary.
Which is newer?
Ministral 14B is the newest, released Dec 2, 2025. Trinity Nano Preview came out Dec 1, 2025; Gemini 2.5 Computer Use Preview came out Oct 7, 2025. Knowledge cutoff: Gemini 2.5 Computer Use Preview Jan 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.
