Gemma 2 27B vs Saba vs Mistral Large
Too close to call on our weighted score (Saba 46, Mistral Large 45, Gemma 2 27B 28). The right pick depends on what you value most.
GoogleGemma 2 27B
28/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
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
Too close to call
It is close. Our weighted score puts them within 1 points (Saba 46/100, Mistral Large 45/100, Gemma 2 27B 28/100), 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 · Gemma 2 27B $0.65 · Mistral Large $0.75 per 1M tokens (3:1 blend)
- Longest contextMistral LargeMistral Large 128,000 · Saba 32,768 · Gemma 2 27B 8,192 tokens
- Widest inputsSaba and Mistral LargeGemma 2 27B: Text · Saba: Text, PDFs · Mistral Large: Text, PDFs
- Self-hostingGemma 2 27BPublishes downloadable weights
| Measure | Weight | Gemma 2 27B | Saba | Mistral Large |
|---|---|---|---|---|
| Price | 50% | 56 | 72 | 53 |
| Inputs & features | 30% | 0 | 35 | 45 |
| Context window | 20% | 0 | 0 | 24 |
| Overall | 100% | 28/100 | 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 | Gemma 2 27BGoogle | SabaMistral AI | Mistral LargeMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.1 (best) | — | 122.0 |
| ECI rank | #152 of 165 (best) | — | #153 of 165 |
| GPQA DiamondGraduate-level science questions | 36.5% | — | 38.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.4% | — | 1.9% (best) |
| Price per million tokens | |||
| Input | $0.65 | $0.20 (best) | $0.50 |
| Output | $0.65 | $0.60 (best) | $1.50 |
| Cached input | — | — | $0.05 |
| Blended (3:1) | $0.65 | $0.30 (best) | $0.75 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 4 providers | Official Mistral API |
| Limits | |||
| Context window | 8,192 tokens | 32,768 tokens | 128,000 tokens (best) |
| Max output | 2,048 tokens | 26,214 tokens | 102,400 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | — | — | mistral-large-latest |
| API providers | 3 | 4 | 11 (best) |
| Released | Jul 13, 2024 | Feb 17, 2025 | Feb 26, 2024 |
| Knowledge cutoff | Jun 30, 2024 | 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.
- Gemma 2 27B$7.80
- Saba$3.20
- Mistral Large$8.00
Which should you choose?
Which is better: Gemma 2 27B, Saba or Mistral Large?
It is close. Our weighted score puts them within 1 points (Saba 46/100, Mistral Large 45/100, Gemma 2 27B 28/100), 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, Gemma 2 27B, Saba or Mistral Large?
Saba is cheaper at $0.20 input / $0.60 output per million tokens (median across 4 API providers). Gemma 2 27B costs $0.65 input / $0.65 output per million tokens (median across 3 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 $0.65 for Gemma 2 27B (2.2× as much) and $0.75 for Mistral Large (2.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemma 2 27B has an ECI of 122.1, 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 Gemma 2 27B, Saba and Mistral Large yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Gemma 2 27B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Mistral Large has the largest context window at 128,000 tokens, against 32,768 for Saba and 8,192 for Gemma 2 27B. Maximum output per response: Gemma 2 27B up to 2,048, Saba up to 26,214, Mistral Large up to 102,400 tokens.
Which can read images, PDFs, audio or video?
Gemma 2 27B accepts text; Saba accepts text and PDFs; Mistral Large accepts text and PDFs. Saba handles the widest range of inputs.
Are any of these open source?
Gemma 2 27B publishes its weights and can be self-hosted; Saba and Mistral Large is proprietary.
Which is newer?
Saba is the newest, released Feb 17, 2025. Gemma 2 27B came out Jul 13, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Gemma 2 27B Jun 30, 2024, 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.
