Llama-3.1-8B-Instruct vs Qwen Turbo vs Ministral 8B Instruct
Qwen Turbo comes out ahead, 57 to 42 and 42 on our weighted score, and it is the cheaper option too.
Meta
Llama-3.1-8B-Instruct
42/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
- Our pick
Alibaba (Qwen)
Qwen Turbo
57/100- ECI—
- Price$0.05 / $0.20
- Context1M
Mistral AI
Ministral 8B Instruct
42/100- ECI—
- Price$0.15 / $0.15
- Context131K
Qwen Turbo is our pick
Qwen Turbo is the better all-round choice, scoring 57/100 against Ministral 8B Instruct (42) and Llama-3.1-8B-Instruct (42). It leads on capability, price, inputs & features and context window. 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 and Ministral 8B Instruct has no Capabilities Index score yet.
- CapabilityQwen TurboShared benchmarks: Qwen Turbo 41.8% · Ministral 8B Instruct 27.2% · Llama-3.1-8B-Instruct 27.0%
- Lowest priceQwen TurboQwen Turbo $0.087 · Ministral 8B Instruct $0.15 · Llama-3.1-8B-Instruct $0.156 per 1M tokens (3:1 blend)
- Longest contextQwen TurboQwen Turbo 1,000,000 · Ministral 8B Instruct 131,072 · Llama-3.1-8B-Instruct 128,000 tokens
- Widest inputsSame inputsLlama-3.1-8B-Instruct: Text · Qwen Turbo: Text · Ministral 8B Instruct: Text
- Self-hostingLlama-3.1-8B-Instruct and Ministral 8B InstructPublishes downloadable weights (Mistral Research License)
| Measure | Weight | Llama-3.1-8B-Instruct | Qwen Turbo | Ministral 8B Instruct |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 27 | 42 | 27 |
| Price | 25% | 88 | 100 | 89 |
| Inputs & features | 15% | 25 | 35 | 25 |
| Context window | 10% | 24 | 60 | 24 |
| Overall | 100% | 42/100 | 57/100 | 42/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 116.6 | — | — |
| ECI rank | #145 of 148 | — | — |
| GPQA DiamondGraduate-level science questions | 27.0% | 41.8% (best) | 27.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.7% | 6.1% (best) | — |
| Price per million tokens | |||
| Input | $0.152 | $0.05 (best) | $0.15 |
| Output | $0.167 | $0.20 | $0.15 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.156 | $0.087 (best) | $0.15 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 9 providers | Official Alibaba API | Median of 1 providers |
| Limits | |||
| Context window | 128,000 tokens | 1,000,000 tokens (best) | 131,072 tokens |
| Max output | 4,096 tokens | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | 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 | OpenMistral Research License |
| API model ID | — | qwen-turbo | — |
| API providers | 9 (best) | 3 | 1 |
| Released | Jul 23, 2024 | Nov 1, 2024 | Oct 16, 2024 |
| Knowledge cutoff | Dec 2023 | 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.
Llama-3.1-8B-Instruct$1.85
Qwen Turbo$0.90
Ministral 8B Instruct$1.80
Which should you choose?
Which is better: Llama-3.1-8B-Instruct, Qwen Turbo or Ministral 8B Instruct?
Qwen Turbo is the better all-round choice, scoring 57/100 against Ministral 8B Instruct (42) and Llama-3.1-8B-Instruct (42). It leads on capability, price, inputs & features and context window. 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 and Ministral 8B Instruct has no Capabilities Index score yet.
Which is cheaper, Llama-3.1-8B-Instruct, Qwen Turbo or Ministral 8B Instruct?
Qwen Turbo is cheaper at $0.05 input / $0.20 output per million tokens (official Alibaba API price). Ministral 8B Instruct costs $0.15 input / $0.15 output per million tokens (median across 1 API provider); 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 $0.087 per million tokens for Qwen Turbo versus $0.15 for Ministral 8B Instruct (1.7× as much) and $0.156 for Llama-3.1-8B-Instruct (1.8× 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 8B Instruct 27.2% and Llama-3.1-8B-Instruct 27.0%. On individual benchmarks: GPQA Diamond — Qwen Turbo 41.8%, Ministral 8B Instruct 27.2%, Llama-3.1-8B-Instruct 27.0%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.1-8B-Instruct, Qwen Turbo and Ministral 8B Instruct 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 Ministral 8B Instruct and 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Llama-3.1-8B-Instruct up to 4,096, Qwen Turbo up to 16,384, Ministral 8B Instruct up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.1-8B-Instruct accepts text; Qwen Turbo accepts text; Ministral 8B Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Llama-3.1-8B-Instruct and Ministral 8B Instruct publishes its weights (Mistral Research License) and can be self-hosted; Qwen Turbo is proprietary.
Which is newer?
Qwen Turbo is the newest, released Nov 1, 2024. Ministral 8B Instruct came out Oct 16, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023, 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.