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DeepSeek V3.2 vs Meta Llama3 1 405b 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
DeepSeek V3.2
Context window
164K
163,840 tokens · ~123K words
Model
Meta Llama3 1 405b 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.
DeepSeek V3.2 has about 1.3× the context window of the other in this pair.
DeepSeek V3.2 has 28% more context capacity (163K vs 128K tokens). DeepSeek V3.2 is 94% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use DeepSeek V3.2. Its 163K context fits entire documents without chunking (vs 128K).
RAG / high-volume retrieval
Use DeepSeek V3.2. Input tokens are 94% cheaper — critical when sending large retrieved contexts.
Long output (reports, code files)
Use DeepSeek V3.2. Its 163K 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 | DeepSeek V3.2 | Meta Llama3 1 405b Instruct |
|---|---|---|
| Context window | 163,840 tokens (163K) | 128,000 tokens (128K) |
| Max output tokens | 163,840 tokens (163K) | 4,096 tokens (4K) |
| Speed tier | Balanced | Deep |
| Vision | No | No |
| Function calling | Yes | Yes |
| Extended thinking | Yes | No |
| Prompt caching | Yes | No |
| Batch API | No | No |
| Release date | Dec 2025 | 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 | DeepSeek V3.2 in | DeepSeek V3.2 out | Meta Llama3 1 405b Instruct in | Meta Llama3 1 405b Instruct out |
|---|---|---|---|---|
| Aws Bedrock | $0.740/M | $2.22/M | $5.32/M | $16.00/M |
| Azure | $0.580/M | $1.68/M | — | — |
| Deepseek | $0.280/M | $0.400/M | — | — |
| Gmi | $0.280/M | $0.400/M | — | — |
| Novita | $0.269/M | $0.400/M | — | — |
| Openrouter | $0.280/M | $0.400/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