Qwen Turbo vs Qwen-VL OCR vs Gemma 3 12B IT
Too close to call on our weighted score (Qwen Turbo 72, Gemma 3 12B IT 70, Qwen-VL OCR 36). The right pick depends on what you value most.
Alibaba (Qwen)
Qwen Turbo
72/100- ECI—
- Price$0.05 / $0.20
- Context1M
Alibaba (Qwen)
Qwen-VL OCR
36/100- ECI—
- Price$0.72 / $0.72
- Context34K
Google
Gemma 3 12B IT
70/100- ECI123.5
- Price$0.05 / $0.15
- Context131K
Too close to call
It is close. Our weighted score puts them within 3 points (Qwen Turbo 72/100, Gemma 3 12B IT 70/100, Qwen-VL OCR 36/100), so choose by what matters most for your work: Gemma 3 12B IT on price and Qwen Turbo 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 priceGemma 3 12B ITGemma 3 12B IT $0.075 · Qwen Turbo $0.087 · Qwen-VL OCR $0.72 per 1M tokens (3:1 blend)
- Longest contextQwen TurboQwen Turbo 1,000,000 · Gemma 3 12B IT 131,072 · Qwen-VL OCR 34,096 tokens
- Widest inputsQwen-VL OCR and Gemma 3 12B ITQwen Turbo: Text · Qwen-VL OCR: Text, Images · Gemma 3 12B IT: Text, Images
- Self-hostingGemma 3 12B ITPublishes downloadable weights
| Measure | Weight | Qwen Turbo | Qwen-VL OCR | Gemma 3 12B IT |
|---|---|---|---|---|
| Price | 50% | 100 | 57 | 100 |
| Inputs & features | 30% | 35 | 25 | 50 |
| Context window | 20% | 60 | 1 | 24 |
| Overall | 100% | 72/100 | 36/100 | 70/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | 123.5 |
| ECI rank | — | — | #138 of 148 |
| GPQA DiamondGraduate-level science questions | 41.8% (best) | — | 39.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 6.1% | — | 16.7% (best) |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.72 | $0.05 (best) |
| Output | $0.20 | $0.72 | $0.15 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.087 | $0.72 | $0.075 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Official Alibaba API | Median of 7 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 34,096 tokens | 131,072 tokens |
| Max output | 16,384 tokens | 4,096 tokens | 131,072 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 | Yes | No | No |
| Tool calling | Yes | No | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | qwen-turbo | qwen-vl-ocr | — |
| API providers | 3 | 1 | 7 (best) |
| Released | Nov 1, 2024 | Oct 28, 2024 | Mar 12, 2025 |
| Knowledge cutoff | Apr 2024 | Apr 2024 | Aug 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Qwen Turbo$0.90
Qwen-VL OCR$8.64
Gemma 3 12B IT$0.80
Which should you choose?
Which is better: Qwen Turbo, Qwen-VL OCR or Gemma 3 12B IT?
It is close. Our weighted score puts them within 3 points (Qwen Turbo 72/100, Gemma 3 12B IT 70/100, Qwen-VL OCR 36/100), so choose by what matters most for your work: Gemma 3 12B IT on price and Qwen Turbo 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, Qwen Turbo, Qwen-VL OCR or Gemma 3 12B IT?
Gemma 3 12B IT is cheaper at $0.05 input / $0.15 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); Qwen-VL OCR costs $0.72 input / $0.72 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.075 per million tokens for Gemma 3 12B IT versus $0.087 for Qwen Turbo (1.2× as much) and $0.72 for Qwen-VL OCR (9.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen Turbo has not been scored yet, Qwen-VL OCR has not been scored yet and Gemma 3 12B IT has an ECI of 123.5.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen Turbo, Qwen-VL OCR and Gemma 3 12B IT yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-VL OCR does not support tool calling, which most coding agents need.
Which has the bigger context window?
Qwen Turbo has the largest context window at 1,000,000 tokens, against 131,072 for Gemma 3 12B IT and 34,096 for Qwen-VL OCR. Maximum output per response: Qwen Turbo up to 16,384, Qwen-VL OCR up to 4,096, Gemma 3 12B IT up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen Turbo accepts text; Qwen-VL OCR accepts text and images; Gemma 3 12B IT accepts text and images. Qwen-VL OCR handles the widest range of inputs.
Are any of these open source?
Gemma 3 12B IT publishes its weights and can be self-hosted; Qwen Turbo and Qwen-VL OCR is proprietary.
Which is newer?
Gemma 3 12B IT is the newest, released Mar 12, 2025. Qwen Turbo came out Nov 1, 2024; Qwen-VL OCR came out Oct 28, 2024. Knowledge cutoff: Qwen Turbo Apr 2024, Qwen-VL OCR Apr 2024, Gemma 3 12B IT Aug 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.