MetaReasoningReleased 25 September 2024

Llama 3.2 3B Instruct pricing, context and benchmark

Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization.

131K
Input context
118K
Output context
$0.05
Official input
$0.33
Official output
n/a
AA index

Everything that matters, in one table

Context, pricing, cache, modalities and tooling, from the model registry and Artificial Analysis.

ModelLlama 3.2 3B Instruct
Model IDmeta-llama/llama-3.2-3b-instruct
ProviderMeta
Release date25 September 2024
StatusGenerally available
Input context131,072 tokens
Output context117,964 tokens
Official input pricing$0.05 per 1M tokens
Official output pricing$0.33 per 1M tokens
Cache read pricingNot published
Market input pricing$0.05 per 1M (cheapest route)
Market output pricing$0.33 per 1M (cheapest route)
Input modalitiestext
Output modalitiestext
Reasoning controlNot exposed
Tool supportText generation only
TokenizerLlama3
Provider routes2 endpoints
Artificial Analysis indexNot published
SpeedNot published
Knowledge cutoffNot publicly stated

Input and output support

ModalityInputOutputBilled at
Text✓ yes✓ yes$0.05 in
Imagenononot supported
Audionononot supported
Videonononot supported
File (PDF)nononot supported

What is Llama 3.2 3B Instruct?

Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization.

Designed with the latest transformer architecture, it...

Llama 3.2 3B Instruct carries a 131K token window, uses the Llama3 tokenizer and is served by Meta. On Hoodgen it sits in the Reasoning tier of the model menu next to its siblings, so you can switch mid conversation without losing the thread.

Release and what changed from the previous version

Released25 September 2024

This is the only release of Llama 3.2 3B Instruct on OpenRouter, released 25 September 2024. The provider has not published a knowledge cutoff, so treat training data as recent but unconfirmed for very new events.

Features and capabilities

{ }
Structured outputs
Schema constrained JSON with response_format, so no parse and retry loop in your code.
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Seeds
A seed can be pinned so the same prompt is reproducible across test runs.

What can you do with Llama 3.2 3B Instruct?

Debugging and root cause
Multi file failures where the model has to hold a causal chain before answering.
Architecture and planning
Design docs, migration plans and trade off analysis over long context.
Data analysis
Spreadsheets and logs read in one pass, then summarised with the numbers quoted back.
Agentic coding
Repo wide changes that need plan, edit and verify loops.

Llama 3.2 3B Instruct pricing

Official pricing

List price
$0.05 / 1M in
$0.33 / 1M out
  • 131K context
  • text input
Cheapest route
$0.05 / 1M in
$0.33 / 1M out
  • 2 routes on OpenRouter
  • What Hoodgen routes to first
  • Same model, lower bill

Market pricing, every route

ProviderTierInputOutputCache readUptime 24h
Parasailstandard$0.05$0.33n/a100.0%
Cloudflarestandard$0.051$0.335n/a100.0%

API pricing and cost calculator

RatePer callTotalCredits
Cheapest route$0.0015$0.75711
List price$0.0015$0.75711

API and developer information

Model IDmeta-llama/llama-3.2-3b-instruct
Endpointhttps://openrouter.ai/api/v1/chat/completions
Parametersfrequency_penalty · logit_bias · logprobs · max_tokens · min_p · presence_penalty · repetition_penalty · seed · stop · structured_outputs · temperature · top_k · top_logprobs · top_p
StreamingYes, server sent events
Modality stringtext->text
Max prompt tokens131,072
Max completion tokens117,964
curl https://openrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "meta-llama/llama-3.2-3b-instruct",
    "messages": [{ "role": "user", "content": "Summarise this document." }],
    "max_tokens": 1024
  }'

Model limitations

Text only outputIt cannot generate images, audio or video. Pair it with an image model on Hoodgen when you need visuals.
Output cap117,964 tokens per request. Long deliverables have to be chunked.
Benchmarks not publishedArtificial Analysis does not publish an Intelligence Index for this release, so no benchmark score is claimed here.
Knowledge cutoffThe provider does not state a fixed cutoff for every release. Verify very recent events against search.

Llama 3.2 3B Instruct vs other Meta models

ModelContextInput /1MOutput /1MAA indexReleased
Llama 3.2 3B Instruct131K$0.05$0.33n/a2024
Muse Wonder1.05M$4$2044Oct 2026
Muse Spark 1.31.05M$1.25$4.2537Sep 2026
Muse Spark Open1.05M$1.25$4.2525Oct 2026
Muse Spark 1.21.05M$1.25$4.25n/a2026
Muse Spark 1.11.05M$1.25$4.25n/a2026

Privacy and data policy

  • On Hoodgen, prompts and attachments answer that request and stay in your conversation history so you can reopen it. They are not used to train models.
  • Requests route through OpenRouter to Meta and are covered by that provider's API terms.
  • Do not paste secrets or personal data you would not send to any hosted model.

Llama 3.2 3B Instruct questions, answered

Llama 3.2 3B Instruct is a reasoning model from Meta, released 25 September 2024. Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization.
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Start chatting with Llama 3.2 3B Instruct

Free to try on Hoodgen AI, with a live credit estimate before every send. No API key, no setup.