Saba vs Mistral Large
Too close to call on our weighted score (Saba 46, Mistral Large 45). The right pick depends on what you value most.
Mistral AISaba
46/100- ECI—
- Price$0.20 / $0.60
- Context33K
- Mistral AI
Mistral Large
45/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 1 points (Saba 46/100, Mistral Large 45/100), so choose by what matters most for your work: Saba on price and Mistral Large for long inputs. 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 priceSabaSaba $0.30 · Mistral Large $0.75 per 1M tokens (3:1 blend)
- Longest contextMistral LargeMistral Large 128,000 · Saba 32,768 tokens
- Widest inputsSame inputsSaba: Text, PDFs · Mistral Large: Text, PDFs
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | Saba | Mistral Large |
|---|---|---|---|
| Price | 50% | 72 | 53 |
| Inputs & features | 30% | 35 | 45 |
| Context window | 20% | 0 | 24 |
| Overall | 100% | 46/100 | 45/100 |
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 | SabaMistral AI | Mistral LargeMistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 122.0 |
| ECI rank | — | #153 of 165 |
| GPQA DiamondGraduate-level science questions | — | 38.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 1.9% |
| Price per million tokens | ||
| Input | $0.20 (best) | $0.50 |
| Output | $0.60 (best) | $1.50 |
| Cached input | — | $0.05 |
| Blended (3:1) | $0.30 (best) | $0.75 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 4 providers | Official Mistral API |
| Limits | ||
| Context window | 32,768 tokens | 128,000 tokens (best) |
| Max output | 26,214 tokens | 102,400 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | Yes | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | — | mistral-large-latest |
| API providers | 4 | 11 (best) |
| Released | Feb 17, 2025 | Feb 26, 2024 |
| Knowledge cutoff | Sep 30, 2024 | Nov 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.
- Saba$3.20
- Mistral Large$8.00
Which should you choose?
Which is better: Saba or Mistral Large?
It is close. Our weighted score puts them within 1 points (Saba 46/100, Mistral Large 45/100), so choose by what matters most for your work: Saba on price and Mistral Large for long inputs. 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, Saba or Mistral Large?
Saba is cheaper at $0.20 input / $0.60 output per million tokens (median across 4 API providers). Mistral Large costs $0.50 input / $1.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.30 per million tokens for Saba versus $0.75 for Mistral Large (2.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Saba has not been scored yet and Mistral Large has an ECI of 122.0.
Which is better for coding?
There are no published SWE-bench Verified results for Saba and Mistral Large yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Mistral Large has the largest context window at 128,000 tokens, against 32,768 for Saba. Maximum output per response: Saba up to 26,214, Mistral Large up to 102,400 tokens.
Which can read images, PDFs, audio or video?
Saba accepts text and PDFs; Mistral Large accepts text and PDFs. They handle the same number of input types.
Are any of these open source?
No. Saba and Mistral Large are proprietary and only available through APIs and apps.
Which is newer?
Saba is the newest, released Feb 17, 2025. Mistral Large came out Feb 26, 2024. Knowledge cutoff: Saba Sep 30, 2024, Mistral Large Nov 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 Nov 2, 2026.
