meta-llama
Meta: Llama 3.2 3B Instruct
meta-llama/llama-3.2-3b-instruct
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter's catalog describes meta-llama/llama-3.2-3b-instruct as a Meta 3-billion-parameter multilingual instruction model for text input and text output, aimed at dialogue, reasoning, and summarization. It reports a 131,072-token context window, a December 2023 knowledge cutoff, and API controls including sampling penalties, logprobs, seeds, stop sequences, and structured outputs. These are catalog-reported characteristics; this source pack contains no independent model card or measured benchmark evidence, so real-world behavior should be validated on the intended workload.[1]
Strengths
- The catalog presents a multilingual, text-only instruction model with 3 billion parameters; its description names dialogue, reasoning, and summarization.[1]
- A reported 131,072-token context window may accommodate long prompts, subject to workload validation.[1]
- Reported API parameters include structured outputs, logprobs, seed, stop, and several sampling controls.[1]
Limitations
- All evidence here comes from OpenRouter's catalog; an independent model card was not available in this source pack.[1]
- No measured benchmark or field results were supplied, so quality, latency, reliability, and cost-effectiveness remain unverified for any workload.[1]
- The reasoning flag is null even though the description mentions reasoning; documented input and output are text only, while license terms, hardware requirements, and safety guarantees are not specified.[1]
Where to use it
- Prototyping multilingual assistants or text chat flows where a 3-billion-parameter, text-only model is acceptable; compare responses before production use.[1]
- Summarizing or drafting over long prompts that could benefit from the reported context window, with tests for recall and coherence.[1]
- Format-constrained extraction or generation using the reported structured-outputs parameter, with schema conformance checks.[1]
Sources
- [1] OpenRouter catalog · Meta: Llama 3.2 3B InstructSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
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...
Specifications
- Model ID
- meta-llama/llama-3.2-3b-instruct
- Creator
- meta-llama
- Added to OpenRouter
- 25.09.2024
- Context length
- 131,072
- Modality
- text->text
- Input modalities
- text
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.050 / out $0.330
- Knowledge cutoff
- 31.12.2023
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | — |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs |
| Writing | No measurement | output: text |
| Reasoning | No measurement | — |
| Document analysis | No measurement | — |
| Vision | No measurement | — |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Parasailbf16 | 131,072 | $0.050 | $0.330 | — | — | 100% |
| Cloudflare | 80,000 | $0.051 | $0.335 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.