Gemma 3 12B IT vs GLM-4.7-Flash vs Qwen Turbo
Too close to call on our weighted score (Gemma 3 12B IT 49, GLM-4.7-Flash 48, Qwen Turbo 48). The right pick depends on what you value most.
GoogleGemma 3 12B IT
49/100- ECI123.5
- Price$0.05 / $0.15
- Context131K
Z.ai (Zhipu)GLM-4.7-Flash
48/100- ECI—
- Price$0.06 / $0.40
- Context200K
Alibaba (Qwen)Qwen Turbo
48/100- ECI—
- Price$0.05 / $0.20
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (Gemma 3 12B IT 49/100, GLM-4.7-Flash 48/100, Qwen Turbo 48/100), so choose by what matters most for your work: GLM-4.7-Flash for raw capability, Gemma 3 12B IT 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 GLM-4.7-Flash and Qwen Turbo has no Capabilities Index score yet.
- CapabilityGLM-4.7-FlashShared benchmarks: GLM-4.7-Flash 35.1% · Gemma 3 12B IT 28.1% · Qwen Turbo 24.0%
- Lowest priceGemma 3 12B ITGemma 3 12B IT $0.075 · Qwen Turbo $0.087 · GLM-4.7-Flash $0.145 per 1M tokens (3:1 blend)
- Longest contextQwen TurboQwen Turbo 1,000,000 · GLM-4.7-Flash 200,000 · Gemma 3 12B IT 131,072 tokens
- Widest inputsGemma 3 12B ITGemma 3 12B IT: Text, Images · GLM-4.7-Flash: Text · Qwen Turbo: Text
- Self-hostingGemma 3 12B IT and GLM-4.7-FlashPublishes downloadable weights
| Measure | Weight | Gemma 3 12B IT | GLM-4.7-Flash | Qwen Turbo |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 28 | 35 | 24 |
| Price | 25% | 100 | 90 | 100 |
| Inputs & features | 15% | 50 | 35 | 35 |
| Context window | 10% | 24 | 32 | 60 |
| Overall | 100% | 49/100 | 48/100 | 48/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemma 3 12B ITGoogle | GLM-4.7-FlashZ.ai (Zhipu) | Qwen TurboAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 123.5 | — | — |
| ECI rank | #138 of 148 | — | — |
| GPQA DiamondGraduate-level science questions | 39.5% | 45.1% (best) | 41.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | 16.7% | 25.0% (best) | 6.1% |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.06 | $0.05 (best) |
| Output | $0.15 (best) | $0.40 | $0.20 |
| Cached input | — | — | — |
| Blended (3:1) | $0.075 (best) | $0.145 | $0.087 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 7 providers | Median of 13 providers | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens | 1,000,000 tokens (best) |
| Max output | 131,072 tokens (best) | 131,072 tokens (best) | 16,384 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 | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | glm-4.7-flash | qwen-turbo |
| API providers | 7 | 19 (best) | 3 |
| Released | Mar 12, 2025 | Jan 19, 2026 | Nov 1, 2024 |
| Knowledge cutoff | Aug 2024 | Apr 2025 | Apr 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 12B IT$0.80
- GLM-4.7-Flash$1.41
- Qwen Turbo$0.90
Which should you choose?
Which is better: Gemma 3 12B IT, GLM-4.7-Flash or Qwen Turbo?
It is close. Our weighted score puts them within a point (Gemma 3 12B IT 49/100, GLM-4.7-Flash 48/100, Qwen Turbo 48/100), so choose by what matters most for your work: GLM-4.7-Flash for raw capability, Gemma 3 12B IT 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 GLM-4.7-Flash and Qwen Turbo has no Capabilities Index score yet.
Which is cheaper, Gemma 3 12B IT, GLM-4.7-Flash or Qwen Turbo?
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); GLM-4.7-Flash costs $0.06 input / $0.40 output per million tokens (median across 13 API providers; free on Z.AI). 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 $0.145 for GLM-4.7-Flash (1.9× 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): GLM-4.7-Flash 35.1%, Gemma 3 12B IT 28.1% and Qwen Turbo 24.0%. On individual benchmarks: GPQA Diamond — GLM-4.7-Flash 45.1%, Qwen Turbo 41.8%, Gemma 3 12B IT 39.5%; OTIS Mock AIME 2024–2025 — GLM-4.7-Flash 25.0%, Gemma 3 12B IT 16.7%, Qwen Turbo 6.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 3 12B IT, GLM-4.7-Flash and Qwen Turbo yet, so there is no like-for-like coding score. On overall capability, GLM-4.7-Flash 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 200,000 for GLM-4.7-Flash and 131,072 for Gemma 3 12B IT. Maximum output per response: Gemma 3 12B IT up to 131,072, GLM-4.7-Flash up to 131,072, Qwen Turbo up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Gemma 3 12B IT accepts text and images; GLM-4.7-Flash accepts text; Qwen Turbo accepts text. Gemma 3 12B IT handles the widest range of inputs.
Are any of these open source?
Gemma 3 12B IT and GLM-4.7-Flash publishes its weights and can be self-hosted; Qwen Turbo is proprietary.
Which is newer?
GLM-4.7-Flash is the newest, released Jan 19, 2026. Gemma 3 12B IT came out Mar 12, 2025; Qwen Turbo came out Nov 1, 2024. Knowledge cutoff: Gemma 3 12B IT Aug 2024, GLM-4.7-Flash Apr 2025, Qwen Turbo Apr 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.
