Context Window

Compare

DeepSeek V3.1 vs Deepseek R1 Distill Qwen 14b

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 V3.1

Tool calling

Context window

164K

163,840 tokens · ~123K words

Model page
Alibaba

Model

Deepseek R1 Distill Qwen 14b

Context window

131K

131,072 tokens · ~98K 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 V3.1164K
Deepseek R1 Distill Qwen 14b131K

DeepSeek V3.1 has about 1.3× the context window of the other in this pair.

Token calculator →Memory savings →

DeepSeek V3.1 has 25% more context capacity (163K vs 131K tokens). Deepseek R1 Distill Qwen 14b is 65% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use DeepSeek V3.1. Its 163K context fits entire documents without chunking (vs 131K).

  • RAG / high-volume retrieval

    Use Deepseek R1 Distill Qwen 14b. Input tokens are 65% 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 V3.1Deepseek R1 Distill Qwen 14b
Context window163,840 tokens (163K)131,072 tokens (131K)
Max output tokens163,840 tokens (163K)N/A
Speed tierBalancedDeep
VisionNoNo
Function callingYesNo
Extended thinkingYesYes
Prompt cachingYesNo
Batch APINoNo
Release dateAug 2025N/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 V3.1 inDeepSeek V3.1 outDeepseek R1 Distill Qwen 14b inDeepseek R1 Distill Qwen 14b out
Fireworks——$0.200/M$0.200/M
Novita——$0.150/M$0.150/M
Nscale——$0.070/M$0.070/M
Openrouter$0.200/M$0.800/M——

Frequently asked questions

DeepSeek V3.1 has a larger context window: 163K tokens vs 131K. 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