Compare
Claude Sonnet 4 6 vs Meta Llama3 2 11b Instruct
This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.
Model
Claude Sonnet 4 6
Context window
1M
1,000,000 tokens · ~750K words
Model
Meta Llama3 2 11b Instruct
Context window
128K
128,000 tokens · ~96K words
Context window · side by side
Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.
Claude Sonnet 4 6 has about 7.8× the context window of the other in this pair.
Claude Sonnet 4 6 has 681% more context capacity (1000K vs 128K tokens). Meta Llama3 2 11b Instruct is 88% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Claude Sonnet 4 6. Its 1000K context fits entire documents without chunking (vs 128K).
RAG / high-volume retrieval
Use Meta Llama3 2 11b Instruct. Input tokens are 88% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use Claude Sonnet 4 6. Its 64K max output lets you generate complete artifacts in one request.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Claude Sonnet 4 6 | Meta Llama3 2 11b Instruct |
|---|---|---|
| Context window | 1,000,000 tokens (1000K) | 128,000 tokens (128K) |
| Max output tokens | 64,000 tokens (64K) | 4,096 tokens (4K) |
| Speed tier | Balanced | Fast |
| Vision | Yes | Yes |
| Function calling | Yes | Yes |
| Extended thinking | Yes | No |
| Prompt caching | Yes | No |
| Batch API | Yes | No |
| Release date | N/A | N/A |
Pricing matrix
Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.
| Provider | Claude Sonnet 4 6 in | Claude Sonnet 4 6 out | Meta Llama3 2 11b Instruct in | Meta Llama3 2 11b Instruct out |
|---|---|---|---|---|
| Anthropic | $3.00/M | $15.00/M | — | — |
| Aws Bedrock | $3.00/M | $15.00/M | $0.350/M | $0.350/M |
| Azure | $3.00/M | $15.00/M | — | — |
| Google Vertex | $3.00/M | $15.00/M | — | — |
| Openrouter | $3.00/M | $15.00/M | — | — |
Frequently asked questions
Powered by Mem0
Use a smaller model.
Get better results.
Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.
Example: a multi-turn chat session
80% less to send — works with any model