Mixtral Turbo 1.5B: pricing, context window and benchmarks
Mixtral Turbo 1.5B is a small open-weight model from Together AI. It offers a 4,096-token context window, costs $0.31 per million input tokens and $1.19 per million output tokens, and averages 47.6 across the index's benchmark suite.
Pricing
Mixtral Turbo 1.5B costs $0.31 per million input tokens and $1.19 per million output tokens. A blended 3:1 input-to-output mix works out to about $0.53 per million tokens. Cached input is listed at $0.04 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $0.31 | per 1M tokens |
| Output | $1.19 | per 1M tokens |
| Cached input | $0.04 | per 1M tokens |
| Blended 3:1 | $0.53 | estimate per 1M tokens |
| 1M in + 1M out | $1.50 | estimate |
Benchmarks
Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 55.1 | 572 | 5th | |
| GPQA Diamond | 45.3 | 565 | 6th | |
| SWE-bench Verified | 30.5 | 581 | 3th | |
| HumanEval | 51.5 | 561 | 7th | |
| MATH-500 | 44.2 | 581 | 3th | |
| AIME 2025 | 34.0 | 573 | 5th | |
| LiveCodeBench | 34.9 | 571 | 5th | |
| IFEval | 58.5 | 581 | 3th | |
| TruthfulQA | 54.1 | 578 | 4th | |
| HellaSwag | 67.0 | 563 | 6th | |
| MMMU | 48.5 | 559 | 7th | |
| Arena Elo | 1178.9 | 577 | 4th |
What Mixtral Turbo 1.5B is good for
Mixtral Turbo 1.5B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $0.31 per million input tokens it can handle a large share of production traffic.
Strengths
- Input price of $0.31 per million tokens is at or below the index median.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
Trade-offs
- Context window of 4,096 tokens is small for long-document work.
- Average benchmark score is below the index median; test it on your own task.
- Less reliable on open-ended reasoning and complex multi-step instructions.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 3 Baseten 1.5B | Baseten | 4096 | $0.42 | 48.2 |
| Nemotron Nano 8B | NVIDIA | 8192 | $0.46 | 48.1 |
| Phi-4 1.5B | Microsoft | 8192 | $0.42 | 48.1 |
| Mixtral 1.5B | Mistral AI | 16384 | $0.36 | 47.7 |
| Mixtral Turbo 1.5B | Together AI | 4096 | $0.31 | 47.6 |
| Nemotron Nano 7B | NVIDIA | 8192 | $0.35 | 47.5 |
FAQ
How much does Mixtral Turbo 1.5B cost?
Mixtral Turbo 1.5B is listed at $0.31 per million input tokens and $1.19 per million output tokens. Cached input is $0.045 per million tokens. A blended 3:1 input-to-output mix is about $0.53 per million tokens.
What is the context window of Mixtral Turbo 1.5B?
Mixtral Turbo 1.5B has a context window of 4,096 tokens and can emit up to 4,096 output tokens per request in this index.
Is Mixtral Turbo 1.5B open weights?
Yes. Mixtral Turbo 1.5B is listed as an open-weight model under a open weights licence.
How does Mixtral Turbo 1.5B score on benchmarks?
Mixtral Turbo 1.5B averages 47.6 across the scored benchmarks in this index, ranking #576 of 600 models. Its strongest relative result is Arena Elo at 1178.9.
What is Mixtral Turbo 1.5B best for?
Mixtral Turbo 1.5B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $0.31 per million input tokens it can handle a large share of production traffic.