Zephyr Instruct: pricing, context window and benchmarks
Zephyr Instruct is a open-weight model from Hugging Face. It offers a 4,096-token context window, costs $1.66 per million input tokens and $6.50 per million output tokens, and averages 62.4 across the index's benchmark suite.
Pricing
Zephyr Instruct costs $1.66 per million input tokens and $6.50 per million output tokens. A blended 3:1 input-to-output mix works out to about $2.87 per million tokens. Cached input is listed at $0.24 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $1.66 | per 1M tokens |
| Output | $6.50 | per 1M tokens |
| Cached input | $0.24 | per 1M tokens |
| Blended 3:1 | $2.87 | estimate per 1M tokens |
| 1M in + 1M out | $8.16 | 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 | 65.8 | 440 | 27th | |
| GPQA Diamond | 59.3 | 412 | 31th | |
| SWE-bench Verified | 51.3 | 412 | 31th | |
| HumanEval | 65.1 | 441 | 27th | |
| MATH-500 | 62.9 | 437 | 27th | |
| AIME 2025 | 56.9 | 405 | 33th | |
| LiveCodeBench | 50.0 | 449 | 25th | |
| IFEval | 71.8 | 433 | 28th | |
| TruthfulQA | 66.4 | 440 | 27th | |
| HellaSwag | 75.7 | 431 | 28th | |
| MMMU | 60.9 | 422 | 30th | |
| Arena Elo | 1301.5 | 416 | 31th |
What Zephyr Instruct is good for
Zephyr Instruct is an open-weight model, so it can be self-hosted or run through a third-party inference provider. That matters for data residency, fine-tuning and long-run cost control. At $1.66 per million input tokens (hosted list price) and a 4,096-token context window, it is a practical option for teams that want more control than a closed API allows.
Strengths
- Input price of $1.66 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.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Hunyuan-Turbo Nano | Tencent | 32768 | $4.65 | 62.7 |
| GPT-NeoX Instruct | EleutherAI | 16384 | $1.52 | 62.6 |
| Zephyr Instruct | Hugging Face | 4096 | $1.66 | 62.4 |
| Kimi K1.5 8B | Moonshot AI | 8192 | $1.54 | 62.2 |
| ERNIE 4.0 Nano | Baidu | 32768 | $4.68 | 62.1 |
| SmolLM3 Chat | Hugging Face | 16384 | $1.61 | 62.1 |
FAQ
How much does Zephyr Instruct cost?
Zephyr Instruct is listed at $1.66 per million input tokens and $6.50 per million output tokens. Cached input is $0.24 per million tokens. A blended 3:1 input-to-output mix is about $2.87 per million tokens.
What is the context window of Zephyr Instruct?
Zephyr Instruct has a context window of 4,096 tokens and can emit up to 4,096 output tokens per request in this index.
Is Zephyr Instruct open weights?
Yes. Zephyr Instruct is listed as an open-weight model under a open weights licence.
How does Zephyr Instruct score on benchmarks?
Zephyr Instruct averages 62.4 across the scored benchmarks in this index, ranking #425 of 600 models. Its strongest relative result is Arena Elo at 1301.5.
What is Zephyr Instruct best for?
Zephyr Instruct is an open-weight model, so it can be self-hosted or run through a third-party inference provider. That matters for data residency, fine-tuning and long-run cost control. At $1.66 per million input tokens (hosted list price) and a 4,096-token context window, it is a practical option for teams that want more control than a closed API allows.