Gemma 3 4B IT vs Qwen Turbo vs Ministral 3B
Qwen Turbo comes out ahead, 57 to 47 and 43 on our weighted score, though Gemma 3 4B IT is 29% cheaper per token.
GoogleGemma 3 4B IT
47/100- ECI116.1
- Price$0.05 / $0.10
- Context131K
- Our pick
Alibaba (Qwen)Qwen Turbo
57/100- ECI—
- Price$0.05 / $0.20
- Context1M
Mistral AIMinistral 3B
43/100- ECI118.1
- Price$0.10 / $0.10
- Context128K
Qwen Turbo is our pick
Qwen Turbo is the better all-round choice, scoring 57/100 against Gemma 3 4B IT (47) and Ministral 3B (43). It leads on capability and context window. Gemma 3 4B IT wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Qwen Turbo has no Capabilities Index score yet.
- CapabilityQwen TurboShared benchmarks: Qwen Turbo 41.8% · Ministral 3B 25.3% · Gemma 3 4B IT 23.2%
- Lowest priceGemma 3 4B ITGemma 3 4B IT $0.063 · Qwen Turbo $0.087 · Ministral 3B $0.10 per 1M tokens (3:1 blend)
- Longest contextQwen TurboQwen Turbo 1,000,000 · Gemma 3 4B IT 131,072 · Ministral 3B 128,000 tokens
- Widest inputsGemma 3 4B ITGemma 3 4B IT: Text, Images · Qwen Turbo: Text · Ministral 3B: Text
- Self-hostingGemma 3 4B IT and Ministral 3BPublishes downloadable weights
| Measure | Weight | Gemma 3 4B IT | Qwen Turbo | Ministral 3B |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 23 | 42 | 25 |
| Price | 25% | 100 | 100 | 97 |
| Inputs & features | 15% | 50 | 35 | 25 |
| Context window | 10% | 24 | 60 | 24 |
| Overall | 100% | 47/100 | 57/100 | 43/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemma 3 4B ITGoogle | Qwen TurboAlibaba (Qwen) | Ministral 3BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 116.1 | — | 118.1 (best) |
| ECI rank | #146 of 148 | — | #144 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 23.2% | 41.8% (best) | 25.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 7.5% (best) | 6.1% | — |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.05 (best) | $0.10 |
| Output | $0.10 (best) | $0.20 | $0.10 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.063 (best) | $0.087 | $0.10 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 7 providers | Official Alibaba API | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens | 1,000,000 tokens (best) | 128,000 tokens |
| Max output | 131,072 tokens (best) | 16,384 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| 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 | — |
| API providers | 7 (best) | 3 | 1 |
| Released | Mar 12, 2025 | Nov 1, 2024 | Oct 16, 2024 |
| Knowledge cutoff | Aug 2024 | Apr 2024 | Mar 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 3 4B IT$0.70
- Qwen Turbo$0.90
- Ministral 3B$1.20
Which should you choose?
Which is better: Gemma 3 4B IT, Qwen Turbo or Ministral 3B?
Qwen Turbo is the better all-round choice, scoring 57/100 against Gemma 3 4B IT (47) and Ministral 3B (43). It leads on capability and context window. Gemma 3 4B IT wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Qwen Turbo has no Capabilities Index score yet.
Which is cheaper, Gemma 3 4B IT, Qwen Turbo or Ministral 3B?
Gemma 3 4B IT is cheaper at $0.05 input / $0.10 output per million tokens (median across 7 API providers). Qwen Turbo costs $0.05 input / $0.20 output per million tokens (official Alibaba API price); Ministral 3B costs $0.10 input / $0.10 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.063 per million tokens for Gemma 3 4B IT versus $0.087 for Qwen Turbo (1.4× as much) and $0.10 for Ministral 3B (1.6× 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): Qwen Turbo 41.8%, Ministral 3B 25.3% and Gemma 3 4B IT 23.2%. On individual benchmarks: GPQA Diamond — Qwen Turbo 41.8%, Ministral 3B 25.3%, Gemma 3 4B IT 23.2%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 3 4B IT, Qwen Turbo and Ministral 3B yet, so there is no like-for-like coding score. On overall capability, Qwen Turbo 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 4B IT and 128,000 for Ministral 3B. Maximum output per response: Gemma 3 4B IT up to 131,072, Qwen Turbo up to 16,384, Ministral 3B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemma 3 4B IT accepts text and images; Qwen Turbo accepts text; Ministral 3B accepts text. Gemma 3 4B IT handles the widest range of inputs.
Are any of these open source?
Gemma 3 4B IT and Ministral 3B publishes its weights and can be self-hosted; Qwen Turbo is proprietary.
Which is newer?
Gemma 3 4B IT is the newest, released Mar 12, 2025. Qwen Turbo came out Nov 1, 2024; Ministral 3B came out Oct 16, 2024. Knowledge cutoff: Gemma 3 4B IT Aug 2024, Qwen Turbo Apr 2024, Ministral 3B Mar 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.
