Gemma 3 27B IT vs Qwen Turbo vs Mistral Small 3.2
Too close to call on our weighted score (Mistral Small 3.2 52, Gemma 3 27B IT 51, Qwen Turbo 48). The right pick depends on what you value most.
Google
Gemma 3 27B IT
51/100- ECI130.0
- Price$0.08 / $0.20
- Context131K
Alibaba (Qwen)
Qwen Turbo
48/100- ECI—
- Price$0.05 / $0.20
- Context1M
Mistral AI
Mistral Small 3.2
52/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
Too close to call
It is close. Our weighted score puts them within a point (Mistral Small 3.2 52/100, Gemma 3 27B IT 51/100, Qwen Turbo 48/100), so choose by what matters most for your work: Mistral Small 3.2 for raw capability, Qwen Turbo on price and Qwen Turbo for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Qwen Turbo has no Capabilities Index score yet.
- CapabilityMistral Small 3.2Shared benchmarks: Mistral Small 3.2 39.7% · Gemma 3 27B IT 35.1% · Qwen Turbo 24.0%
- Lowest priceQwen TurboQwen Turbo $0.087 · Gemma 3 27B IT $0.11 · Mistral Small 3.2 $0.15 per 1M tokens (3:1 blend)
- Longest contextQwen TurboQwen Turbo 1,000,000 · Gemma 3 27B IT 131,072 · Mistral Small 3.2 128,000 tokens
- Widest inputsGemma 3 27B IT and Mistral Small 3.2Gemma 3 27B IT: Text, Images · Qwen Turbo: Text · Mistral Small 3.2: Text, Images
- Self-hostingGemma 3 27B IT and Mistral Small 3.2Publishes downloadable weights
| Measure | Weight | Gemma 3 27B IT | Qwen Turbo | Mistral Small 3.2 |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 35 | 24 | 40 |
| Price | 25% | 95 | 100 | 89 |
| Inputs & features | 15% | 50 | 35 | 50 |
| Context window | 10% | 24 | 60 | 24 |
| Overall | 100% | 51/100 | 48/100 | 52/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 130.0 | — | 131.7 (best) |
| ECI rank | #125 of 148 | — | #123 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 47.7% | 41.8% | 49.1% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 22.5% | 6.1% | 30.3% (best) |
| Price per million tokens | |||
| Input | $0.08 | $0.05 (best) | $0.10 |
| Output | $0.20 (best) | $0.20 (best) | $0.30 |
| Cached input | — | — | — |
| Blended (3:1) | $0.11 | $0.087 (best) | $0.15 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 9 providers | Official Alibaba API | Official Mistral API |
| Limits | |||
| Context window | 131,072 tokens | 1,000,000 tokens (best) | 128,000 tokens |
| Max output | 131,072 tokens (best) | 16,384 tokens | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | 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 | Open | Proprietary | Open |
| API model ID | — | qwen-turbo | mistral-small-2506 |
| API providers | 10 (best) | 3 | 6 |
| Released | Mar 12, 2025 | Nov 1, 2024 | Jun 20, 2025 |
| Knowledge cutoff | Aug 2024 | Apr 2024 | Mar 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Gemma 3 27B IT$1.20
Qwen Turbo$0.90
Mistral Small 3.2$1.60
Which should you choose?
Which is better: Gemma 3 27B IT, Qwen Turbo or Mistral Small 3.2?
It is close. Our weighted score puts them within a point (Mistral Small 3.2 52/100, Gemma 3 27B IT 51/100, Qwen Turbo 48/100), so choose by what matters most for your work: Mistral Small 3.2 for raw capability, Qwen Turbo on price and Qwen Turbo for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Qwen Turbo has no Capabilities Index score yet.
Which is cheaper, Gemma 3 27B IT, Qwen Turbo or Mistral Small 3.2?
Qwen Turbo is cheaper at $0.05 input / $0.20 output per million tokens (official Alibaba API price). Gemma 3 27B IT costs $0.08 input / $0.20 output per million tokens (median across 9 API providers); Mistral Small 3.2 costs $0.10 input / $0.30 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.087 per million tokens for Qwen Turbo versus $0.11 for Gemma 3 27B IT (1.3× as much) and $0.15 for Mistral Small 3.2 (1.7× as much).
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): Mistral Small 3.2 39.7%, Gemma 3 27B IT 35.1% and Qwen Turbo 24.0%. On individual benchmarks: GPQA Diamond — Mistral Small 3.2 49.1%, Gemma 3 27B IT 47.7%, Qwen Turbo 41.8%; OTIS Mock AIME 2024–2025 — Mistral Small 3.2 30.3%, Gemma 3 27B IT 22.5%, Qwen Turbo 6.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 3 27B IT, Qwen Turbo and Mistral Small 3.2 yet, so there is no like-for-like coding score. On overall capability, Mistral Small 3.2 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?
Qwen Turbo has the largest context window at 1,000,000 tokens, against 131,072 for Gemma 3 27B IT and 128,000 for Mistral Small 3.2. Maximum output per response: Gemma 3 27B IT up to 131,072, Qwen Turbo up to 16,384, Mistral Small 3.2 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Gemma 3 27B IT accepts text and images; Qwen Turbo accepts text; Mistral Small 3.2 accepts text and images. Gemma 3 27B IT handles the widest range of inputs.
Are any of these open source?
Gemma 3 27B IT and Mistral Small 3.2 publishes its weights and can be self-hosted; Qwen Turbo is proprietary.
Which is newer?
Mistral Small 3.2 is the newest, released Jun 20, 2025. Gemma 3 27B IT came out Mar 12, 2025; Qwen Turbo came out Nov 1, 2024. Knowledge cutoff: Gemma 3 27B IT Aug 2024, Qwen Turbo Apr 2024, Mistral Small 3.2 Mar 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.