Llama 3 Hyperbolic Instruct: pricing, context window and benchmarks
Llama 3 Hyperbolic Instruct is a multimodal model from Hyperbolic. It offers a 200,000-token context window, costs $3.79 per million input tokens and $16.16 per million output tokens, and averages 76.2 across the index's benchmark suite.
Pricing
Llama 3 Hyperbolic Instruct costs $3.79 per million input tokens and $16.16 per million output tokens. A blended 3:1 input-to-output mix works out to about $6.88 per million tokens. Cached input is listed at $0.37 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $3.79 | per 1M tokens |
| Output | $16.16 | per 1M tokens |
| Cached input | $0.37 | per 1M tokens |
| Blended 3:1 | $6.88 | estimate per 1M tokens |
| 1M in + 1M out | $19.95 | 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 | 78.9 | 212 | 65th | |
| GPQA Diamond | 70.1 | 256 | 57th | |
| SWE-bench Verified | 66.2 | 189 | 69th | |
| HumanEval | 79.4 | 251 | 58th | |
| MATH-500 | 81.2 | 186 | 69th | |
| AIME 2025 | 70.4 | 251 | 58th | |
| LiveCodeBench | 69.0 | 208 | 65th | |
| IFEval | 83.6 | 223 | 63th | |
| TruthfulQA | 79.4 | 203 | 66th | |
| HellaSwag | 85.9 | 219 | 64th | |
| MMMU | 74.1 | 185 | 69th | |
| Arena Elo | 1385.7 | 264 | 56th |
What Llama 3 Hyperbolic Instruct is good for
Llama 3 Hyperbolic 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 $3.79 per million input tokens (hosted list price) and a 200,000-token context window, it is a practical option for teams that want more control than a closed API allows.
Strengths
- Large 200,000-token context window for long documents and agent traces.
- Input price of $3.79 per million tokens is at or below the index median.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
- Accepts more than text, including image input where the provider supports it.
Trade-offs
- No standout weakness in the indexed specifications, but real-world behaviour still needs testing.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| Llama 3.1 | Meta AI | 200000 | $4.16 | 76.3 |
| Command R+ Instruct | Cohere | 200000 | $4.16 | 76.2 |
| Llama 3 Baseten Instruct | Baseten | 200000 | $3.91 | 76.2 |
| Llama 3 Hyperbolic Instruct | Hyperbolic | 200000 | $3.79 | 76.2 |
| Sonar Reasoning | Perplexity | 200000 | $11.48 | 76.2 |
| o3 Mini | OpenAI | 128000 | $10.68 | 76.2 |
FAQ
How much does Llama 3 Hyperbolic Instruct cost?
Llama 3 Hyperbolic Instruct is listed at $3.79 per million input tokens and $16.16 per million output tokens. Cached input is $0.37 per million tokens. A blended 3:1 input-to-output mix is about $6.88 per million tokens.
What is the context window of Llama 3 Hyperbolic Instruct?
Llama 3 Hyperbolic Instruct has a context window of 200,000 tokens and can emit up to 65,536 output tokens per request in this index.
Is Llama 3 Hyperbolic Instruct open weights?
Yes. Llama 3 Hyperbolic Instruct is listed as an open-weight model under a open weights licence.
How does Llama 3 Hyperbolic Instruct score on benchmarks?
Llama 3 Hyperbolic Instruct averages 76.2 across the scored benchmarks in this index, ranking #215 of 600 models. Its strongest relative result is Arena Elo at 1385.7.
What is Llama 3 Hyperbolic Instruct best for?
Llama 3 Hyperbolic 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 $3.79 per million input tokens (hosted list price) and a 200,000-token context window, it is a practical option for teams that want more control than a closed API allows.