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Deepseek R1 Distill Llama 8b vs Gpt 5 2 Chat Latest
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 R1 Distill Llama 8b
Context window
131K
131,072 tokens · ~98K words
Model
Gpt 5 2 Chat Latest
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 R1 Distill Llama 8b has about 1× the context window of the other in this pair.
Deepseek R1 Distill Llama 8b has 2% more context capacity (131K vs 128K tokens). Deepseek R1 Distill Llama 8b is 98% cheaper on input.
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Deepseek R1 Distill Llama 8b. Its 131K context fits entire documents without chunking (vs 128K).
RAG / high-volume retrieval
Use Deepseek R1 Distill Llama 8b. Input tokens are 98% cheaper — critical when sending large retrieved contexts.
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Deepseek R1 Distill Llama 8b | Gpt 5 2 Chat Latest |
|---|---|---|
| Context window | 131,072 tokens (131K) | 128,000 tokens (128K) |
| Max output tokens | N/A | 16,384 tokens (16K) |
| Speed tier | Fast | Balanced |
| Vision | No | Yes |
| Function calling | No | Yes |
| Extended thinking | No | Yes |
| Prompt caching | No | Yes |
| Batch API | No | 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 | Deepseek R1 Distill Llama 8b in | Deepseek R1 Distill Llama 8b out | Gpt 5 2 Chat Latest in | Gpt 5 2 Chat Latest out |
|---|---|---|---|---|
| Fireworks | $0.200/M | $0.200/M | — | — |
| Nscale | $0.025/M | $0.025/M | — | — |
| Openai | — | — | $1.75/M | $14.00/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