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Meta-Llama-3.1-8B-Instruct

sambanova · chat model

Meta-Llama-3.1-8B-Instruct is listed here as a chat model from sambanova. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Input
$0.1000 / 1M tokens
Output
$0.2000 / 1M tokens
Cached input
N/A
Context
16.4K

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
$0.2000 / 1M tokens
Embedding
$0.1000 / 1M tokens

Token limits

Context window
16.4K
Max input tokens
16.4K
Max output tokens
16.4K
Max tokens
16.4K

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

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Comparing from
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Meta-Llama-3.1-8B-Instruct
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In $0.1000 / 1M tokens
Out $0.2000 / 1M tokens
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Reference row

Overall blends cost, modality overlap, capabilities, and context.

Model Cost Input shape Features Context Why it is close
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Out $0.2000 / 1M tokens
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Out $0.1400 / 1M tokens
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mistral-small
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In $0.1000 / 1M tokens
Out $0.3000 / 1M tokens
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gpt-4o-mini
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Out $0.6000 / 1M tokens
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Function callingTool choiceResponse schema
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devstral-small-2505
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In $0.1000 / 1M tokens
Out $0.3000 / 1M tokens
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Function callingTool choiceResponse schema
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Partial I/O overlap
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devstral-small-2507
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In $0.1000 / 1M tokens
Out $0.3000 / 1M tokens
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Output: text
Function callingTool choiceResponse schema
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Overall 43%
kimi-k2-instruct
fireworks_ai
In $0.6000 / 1M tokens
Out $2.5000 / 1M tokens
text
Output: text
Function callingTool choiceResponse schema
16.4K
Partial I/O overlap
Overall 42%
devstral-small-latest
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In $0.1000 / 1M tokens
Out $0.3000 / 1M tokens
text
Output: text
Function callingTool choiceResponse schema
256.0K
Partial I/O overlap
Overall 42%
labs-devstral-small-2512
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In $0.1000 / 1M tokens
Out $0.3000 / 1M tokens
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Function callingTool choiceResponse schema
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llama-v3p1-405b-instruct
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In $3.0000 / 1M tokens
Out $3.0000 / 1M tokens
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Function callingTool choiceResponse schema
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Meta-Llama-3.1-405B-Instruct
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In $5.0000 / 1M tokens
Out $10.0000 / 1M tokens
Output: unknown
Function callingTool choiceResponse schema
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Out $0.2000 / 1M tokens
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kimi-k2-instruct-0905
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In $0.6000 / 1M tokens
Out $2.5000 / 1M tokens
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Output: text
Function callingTool choiceResponse schema
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Partial I/O overlap
Overall 35%
gemma-3-27b-it
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Out $0.2000 / 1M tokens
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Low overlap
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lfm-40b
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In $0.1000 / 1M tokens
Out $0.2000 / 1M tokens
Output: unknown
Function callingTool choice
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In $0.3000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Function callingTool choiceResponse schema
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Partial I/O overlap
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ui-tars-1.5-7b
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In $0.1000 / 1M tokens
Out $0.2000 / 1M tokens
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Out $1.2000 / 1M tokens
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Out $0.2000 / 1M tokens
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Response schema
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Out $0.3000 / 1M tokens
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Out $0.8000 / 1M tokens
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