meta-llama-3.1-8b-instruct
friendliai · chat model
meta-llama-3.1-8b-instruct is listed here as a chat model from friendliai. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.
Quick read
Best for
Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.
Things to verify
Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.
Pricing
| Item | Price |
|---|---|
| Input | $0.1000 / 1M tokens |
| Output | $0.1000 / 1M tokens |
| Embedding | $0.1000 / 1M tokens |
Token limits
Capabilities
| Capability | Supported |
|---|---|
| Vision | — |
| Function calling | ✅ |
| Parallel function calling | ✅ |
| Tool choice | ✅ |
| Prompt caching | — |
| Reasoning | — |
| Response schema | ✅ |
| System messages | ✅ |
| Audio input | — |
| Audio output | — |
| Web search | — |
| PDF input | — |
| Video input | — |
Benchmarks
Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer
| Benchmark | Score | Metric | Scope | Checked | Source |
|---|---|---|---|---|---|
| MMLU (CoT) | 88.6 | macro_avg/acc | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| MMLU-Pro (CoT) | 73.3 | macro_avg/acc | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| GPQA Diamond | 49.0 | acc | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| HumanEval | 89.0 | pass@1 | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| MATH (CoT) | 73.8 | sympy_intersection_score | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| MMLU | 85.2 | macro_avg/acc_char | Base model: Llama 3.1 (Llama 3.1 405B) | 2026-05-31 | Link |
| MMLU-Pro (CoT) | 61.6 | macro_avg/acc_char | Base model: Llama 3.1 (Llama 3.1 405B) | 2026-05-31 | Link |
| AGIEval English | 71.6 | average/acc_char | Base model: Llama 3.1 (Llama 3.1 405B) | 2026-05-31 | Link |
| MMLU | 87.3 | macro_avg/acc | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| MMLU (CoT) | 88.6 | macro_avg/acc | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| MMLU-Pro (CoT) | 73.3 | micro_avg/acc_char | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| IFEval | 88.6 | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link | |
| ARC-Challenge | 96.9 | acc | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| GPQA | 50.7 | em | Base model: Llama 3.1 (Llama 3.1 405B Instruct) | 2026-05-31 | Link |
| MMLU | 69.4% | macro_avg/acc | Base model: Llama 3.1 (Llama-3.1-8B-Instruct) | 2026-05-31 | Link |
| MMLU | 83.6% | macro_avg/acc | Base model: Llama 3.1 (Llama-3.1-70B-Instruct) | 2026-05-31 | Link |
| HumanEval | 72.6% | pass@1 | Base model: Llama 3.1 (Llama-3.1-8B-Instruct) | 2026-05-31 | Link |
| HumanEval | 80.5% | pass@1 | Base model: Llama 3.1 (Llama-3.1-70B-Instruct) | 2026-05-31 | Link |
| GSM8K (CoT) | 84.5% | em_maj1@1 | Base model: Llama 3.1 (Llama-3.1-8B-Instruct) | 2026-05-31 | Link |
| GSM8K (CoT) | 95.1% | em_maj1@1 | Base model: Llama 3.1 (Llama-3.1-70B-Instruct) | 2026-05-31 | Link |
| BFCL | 76.1% | acc | Base model: Llama 3.1 (Llama-3.1-8B-Instruct) | 2026-05-31 | Link |
| BFCL | 84.8% | acc | Base model: Llama 3.1 (Llama-3.1-70B-Instruct) | 2026-05-31 | Link |
| Artificial Analysis Intelligence Index | 12.2 | score | Base model: llama-3.1 (meta-llama/llama-3.1-70b-instruct) | 2026-05-31 | Link |
| Artificial Analysis Coding Index | 10.9 | score | Base model: llama-3.1 (meta-llama/llama-3.1-70b-instruct) | 2026-05-31 | Link |
| Artificial Analysis Agentic Index | 5.1 | score | Base model: llama-3.1 (meta-llama/llama-3.1-70b-instruct) | 2026-05-31 | Link |
Sources
| Source links | |
| Pricing data | LiteLLM model cost map |
| Synced at | 2026-05-28 |
Similar models
This list is ranked by overall similarity. Use filters to emphasize the lens that matters most for the replacement you are making.
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| meta-llama-3.1-8b-instruct friendliai | In $0.1000 / 1M tokens Out $0.1000 / 1M tokens |
Output: unknown | Function callingParallel function callingTool choiceResponse schema | 8.2K | Current model Reference row |
| Model | Cost | Input shape | Features | Context | Why it is close |
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| llama-4-maverick-17b-128e-instruct-fp8 lambda_ai | In $0.0500 / 1M tokens Out $0.1000 / 1M tokens |
Output: unknown | Function callingParallel function callingTool choiceSystem messages | 8.2K | Partial I/O overlap Overall 51% |
| llama-4-scout-17b-16e-instruct lambda_ai | In $0.0500 / 1M tokens Out $0.1000 / 1M tokens |
Output: unknown | Function callingParallel function callingTool choiceSystem messages | 8.2K | Partial I/O overlap Overall 51% |
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Output: text | Function callingParallel function callingTool choiceResponse schema | 8.2K | Partial I/O overlap Overall 45% |
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Output: text | Function callingSystem messages | 8.2K | Partial I/O overlap Overall 45% |
| ernie-4.5-21B-a3b novita | In $0.0700 / 1M tokens Out $0.2800 / 1M tokens | text
Output: text | Function callingParallel function callingTool choiceSystem messages | 8.0K | Partial I/O overlap Overall 45% |
| hermes-2-pro-llama-3-8b novita | In $0.1400 / 1M tokens Out $0.1400 / 1M tokens | text
Output: text | Tool choiceResponse schemaSystem messages | 8.2K | Partial I/O overlap Overall 44% |
| meta-llama-3.1-70b-instruct friendliai | In $0.6000 / 1M tokens Out $0.6000 / 1M tokens |
Output: unknown | Function callingParallel function callingTool choiceResponse schema | 8.2K | Same provider Overall 43% |
| qwen2.5-7b-instruct novita | In $0.0700 / 1M tokens Out $0.0700 / 1M tokens | text
Output: text | Function callingParallel function callingTool choiceResponse schema | 32.0K | Partial I/O overlap Overall 43% |
| qwen3-235b-a22b-instruct-2507 novita | In $0.0900 / 1M tokens Out $0.5800 / 1M tokens | text
Output: text | Function callingParallel function callingTool choiceResponse schema | 16.4K | Partial I/O overlap Overall 42% |
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Output: text | Function callingParallel function callingTool choiceResponse schema | 32.8K | Partial I/O overlap Overall 35% |
| llama-v3p1-8b-instruct fireworks_ai | In $0.1000 / 1M tokens Out $0.1000 / 1M tokens | text
Output: text | Response schema | 16.4K | Partial I/O overlap Overall 33% |
| llama-v3p2-1b-instruct fireworks_ai | In $0.1000 / 1M tokens Out $0.1000 / 1M tokens | text
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| deepseek-v3-0324 novita | In $0.2700 / 1M tokens Out $1.1200 / 1M tokens | text
Output: text | Function callingParallel function callingTool choiceResponse schema | 163.8K | Partial I/O overlap Overall 30% |
| kat-coder-pro novita | In $0.3000 / 1M tokens Out $1.2000 / 1M tokens | text
Output: text | Function callingParallel function callingTool choiceResponse schema | 128.0K | Partial I/O overlap Overall 30% |
| minimax-m2.1 novita | In $0.3000 / 1M tokens Out $1.2000 / 1M tokens | text
Output: text | Function callingParallel function callingTool choiceResponse schema | 131.1K | Partial I/O overlap Overall 30% |
| qwen3-max novita | In $2.1100 / 1M tokens Out $8.4500 / 1M tokens | text
Output: text | Function callingParallel function callingTool choiceResponse schema | 65.5K | Partial I/O overlap Overall 27% |
| kimi-k2-0905 novita | In $0.6000 / 1M tokens Out $2.5000 / 1M tokens | text
Output: text | Function callingParallel function callingTool choiceResponse schema | 262.1K | Partial I/O overlap Overall 27% |
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