Qwen Turbo vs Llama-3.1-8B-Instruct vs Gemma 3 12B IT
Too close to call on our weighted score (Gemma 3 12B IT 49, Qwen Turbo 48, Llama-3.1-8B-Instruct 35). The right pick depends on what you value most.
Alibaba (Qwen)
Qwen Turbo
48/100- ECI—
- Price$0.05 / $0.20
- Context1M
Meta
Llama-3.1-8B-Instruct
35/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
Google
Gemma 3 12B IT
49/100- ECI123.5
- Price$0.05 / $0.15
- Context131K
Too close to call
It is close. Our weighted score puts them within a point (Gemma 3 12B IT 49/100, Qwen Turbo 48/100, Llama-3.1-8B-Instruct 35/100), so choose by what matters most for your work: Gemma 3 12B IT for raw capability 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.
- CapabilityGemma 3 12B ITShared benchmarks: Gemma 3 12B IT 28.1% · Qwen Turbo 24.0% · Llama-3.1-8B-Instruct 14.3%
- Lowest priceGemma 3 12B ITGemma 3 12B IT $0.075 · Qwen Turbo $0.087 · Llama-3.1-8B-Instruct $0.156 per 1M tokens (3:1 blend)
- Longest contextQwen TurboQwen Turbo 1,000,000 · Gemma 3 12B IT 131,072 · Llama-3.1-8B-Instruct 128,000 tokens
- Widest inputsGemma 3 12B ITQwen Turbo: Text · Llama-3.1-8B-Instruct: Text · Gemma 3 12B IT: Text, Images
- Self-hostingLlama-3.1-8B-Instruct and Gemma 3 12B ITPublishes downloadable weights
| Measure | Weight | Qwen Turbo | Llama-3.1-8B-Instruct | Gemma 3 12B IT |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 24 | 14 | 28 |
| Price | 25% | 100 | 88 | 100 |
| Inputs & features | 15% | 35 | 25 | 50 |
| Context window | 10% | 60 | 24 | 24 |
| Overall | 100% | 48/100 | 35/100 | 49/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 116.6 | 123.5 (best) |
| ECI rank | — | #145 of 148 | #138 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 41.8% (best) | 27.0% | 39.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 6.1% | 1.7% | 16.7% (best) |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.152 | $0.05 (best) |
| Output | $0.20 | $0.167 | $0.15 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.087 | $0.156 | $0.075 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 9 providers | Median of 7 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 128,000 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 | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | qwen-turbo | — | — |
| API providers | 3 | 9 (best) | 7 |
| Released | Nov 1, 2024 | Jul 23, 2024 | Mar 12, 2025 |
| Knowledge cutoff | Apr 2024 | Dec 2023 | 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
Llama-3.1-8B-Instruct$1.85
Gemma 3 12B IT$0.80
Which should you choose?
Which is better: Qwen Turbo, Llama-3.1-8B-Instruct or Gemma 3 12B IT?
It is close. Our weighted score puts them within a point (Gemma 3 12B IT 49/100, Qwen Turbo 48/100, Llama-3.1-8B-Instruct 35/100), so choose by what matters most for your work: Gemma 3 12B IT for raw capability 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, Qwen Turbo, Llama-3.1-8B-Instruct 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); Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers). 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 $0.156 for Llama-3.1-8B-Instruct (2.1× 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): Gemma 3 12B IT 28.1%, Qwen Turbo 24.0% and Llama-3.1-8B-Instruct 14.3%. On individual benchmarks: GPQA Diamond — Qwen Turbo 41.8%, Gemma 3 12B IT 39.5%, Llama-3.1-8B-Instruct 27.0%; OTIS Mock AIME 2024–2025 — Gemma 3 12B IT 16.7%, Qwen Turbo 6.1%, Llama-3.1-8B-Instruct 1.7%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen Turbo, Llama-3.1-8B-Instruct and Gemma 3 12B IT yet, so there is no like-for-like coding score. On overall capability, Gemma 3 12B IT 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 12B IT and 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Qwen Turbo up to 16,384, Llama-3.1-8B-Instruct 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; Llama-3.1-8B-Instruct accepts text; Gemma 3 12B IT accepts text and images. Gemma 3 12B IT handles the widest range of inputs.
Are any of these open source?
Llama-3.1-8B-Instruct and Gemma 3 12B IT publishes its weights and can be self-hosted; Qwen Turbo is proprietary.
Which is newer?
Gemma 3 12B IT is the newest, released Mar 12, 2025. Qwen Turbo came out Nov 1, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Qwen Turbo Apr 2024, Llama-3.1-8B-Instruct Dec 2023, 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.