Context Window

Compare

DeepSeek V4 Flash Latest vs Llama 3 8b Chat

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.

Deepseek

Model

DeepSeek V4 Flash Latest

Tool calling

Context window

1.3M

1,310,720 tokens · ~983K words

Model page
Meta

Model

Llama 3 8b Chat

Context window

8K

8,192 tokens · ~6K words

Model page

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 V4 Flash Latest1.3M
Llama 3 8b Chat8K

DeepSeek V4 Flash Latest has about 160× the context window of the other in this pair.

Token calculator →Memory savings →

DeepSeek V4 Flash Latest has 15900% more context capacity (1310K vs 8K tokens). DeepSeek V4 Flash Latest is 80% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use DeepSeek V4 Flash Latest. Its 1310K context fits entire documents without chunking (vs 8K).

  • RAG / high-volume retrieval

    Use DeepSeek V4 Flash Latest. Input tokens are 80% cheaper — critical when sending large retrieved contexts.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecDeepSeek V4 Flash LatestLlama 3 8b Chat
Context window1,310,720 tokens (1310K)8,192 tokens (8K)
Max output tokens393,216 tokens (393K)N/A
Speed tierFastFast
VisionNoNo
Function callingYesNo
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateAug 2026N/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.

ProviderDeepSeek V4 Flash Latest inDeepSeek V4 Flash Latest outLlama 3 8b Chat inLlama 3 8b Chat out
Openrouter$0.040/M$0.640/M——
Together Ai——$0.200/M$0.200/M

Frequently asked questions

DeepSeek V4 Flash Latest has a larger context window: 1310K tokens vs 8K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

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.

Calculate your savingsLearn about Mem0

Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model