Compare

Nous Hermes 2 Yi 34b vs Qwen2 Audio 7b

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.

01 Ai

Model

Nous Hermes 2 Yi 34b

Context window

4K

4,096 tokens · ~3K words

Model page
Alibaba

Model

Qwen2 Audio 7b

Context window

4K

4,096 tokens · ~3K 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.

Nous Hermes 2 Yi 34b4K
Qwen2 Audio 7b4K

Same context window size for both models.

Nous Hermes 2 Yi 34b and Qwen2 Audio 7b have identical context windows (4K tokens). Qwen2 Audio 7b is 44% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Qwen2 Audio 7b. Input tokens are 44% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecNous Hermes 2 Yi 34bQwen2 Audio 7b
Context window4,096 tokens (4K)4,096 tokens (4K)
Max output tokens4,096 tokens (4K)4,096 tokens (4K)
Speed tierBalancedFast
VisionNoNo
Function callingNoNo
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/AN/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.

ProviderNous Hermes 2 Yi 34b inNous Hermes 2 Yi 34b outQwen2 Audio 7b inQwen2 Audio 7b out
Fireworks$0.900/M$0.900/M
Sambanova$0.500/M$100.00/M

Frequently asked questions

Qwen2 Audio 7b has a larger context window: 4K tokens vs 4K. 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.

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