LLM Pricing

meta.llama3-70b-instruct-v1:0

Bedrock · Chat model

meta.llama3-70b-instruct-v1:0 is listed here as a chat model from Bedrock. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Provider and model identifiers are kept in their original form for accuracy.

bedrock-bedrock-us-gov-west-1-meta-llama3-70b-instruct-v1-0

Input
$2.6500 / 1M tokens
Output
$3.5000 / 1M tokens
Cached input
$0.2650 / 1M tokens
Context window
2.0K

Catalog generated: Aug 10, 2026

Compare this model Open a side-by-side table using this route and a close match from the current catalog. Estimate cost Use token counts, request volume, and cache assumptions to check a realistic monthly bill.

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
$2.6500 / 1M tokens
Output
$3.5000 / 1M tokens
Cached input
$0.2650 / 1M tokens
Embedding
$2.6500 / 1M tokens

Limits

Context window
2.0K
Max input tokens
8.0K
Max output tokens
2.0K
Max tokens
2.0K
Explore benchmarks Review benchmark rows by family and benchmark label without cross-benchmark ranking. Check data sources See how pricing data is generated and what still needs provider verification. API vs subscription Learn when API pricing matters compared with ChatGPT, Claude Code, Cursor, or Copilot subscriptions. Cache and batch pricing Understand cached input, cache write, batch, priority, and flex pricing rows shown on this page.

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 Supported
Video input -
Native streaming -
Computer use -
Assistant prefill -
Structured output -
Output config -
URL context -

Benchmarks

Most benchmark rows are attached to the base model family rather than this provider route.

Benchmark Score Metric Scope Checked Source
MMLU 82 accuracy Model route 2026-07-15 Link
GPQA 39.5 accuracy Model route 2026-07-15 Link
HumanEval 81.7 pass@1 Model route 2026-07-15 Link
GSM8K 93 accuracy Model route 2026-07-15 Link
MATH 50.4 accuracy Model route 2026-07-15 Link

Related articles

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A four-tier Budget, Mid, Premium, and Reasoning model selection framework for routing queries to the lowest-cost suitable tier.

Hidden Costs of LLM APIs

Fine-tuning, rate limits, latency tradeoffs, evaluation, integration, and vendor risk — the LLM API costs that don't show up in per-token comparisons.

Output vs Input Pricing Multiplier

Output tokens cost 3.6× more than input on average across 2,076 chat models. Provider breakdowns, reasoning vs non-reasoning, and real workload estimates.

Sources

Source links
Pricing dataLiteLLM model cost map
Synced at2026-05-28
Catalog generated2026-08-10T21:27:29.020Z