Context Window

Compare

Granite 4 H Small vs Qwen2.5 Coder 32B 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.

Ibm

Model

Granite 4 H Small

Tool calling

Context window

20K

20,480 tokens · ~15K words

Model page
Alibaba

Model

Qwen2.5 Coder 32B Instruct

Context window

34K

33,792 tokens · ~25K 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.

Granite 4 H Small20K
Qwen2.5 Coder 32B Instruct34K

Qwen2.5 Coder 32B Instruct has about 1.7× the context window of the other in this pair.

Token calculator →Memory savings →

Qwen2.5 Coder 32B Instruct has 65% more context capacity (33K vs 20K tokens). Granite 4 H Small is 66% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Qwen2.5 Coder 32B Instruct. Its 33K context fits entire documents without chunking (vs 20K).

  • RAG / high-volume retrieval

    Use Granite 4 H Small. Input tokens are 66% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Qwen2.5 Coder 32B Instruct. Its 33K 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.

SpecGranite 4 H SmallQwen2.5 Coder 32B Instruct
Context window20,480 tokens (20K)33,792 tokens (33K)
Max output tokens20,480 tokens (20K)33,792 tokens (33K)
Speed tierBalancedBalanced
VisionNoNo
Function callingYesNo
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateN/ANov 2024

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.

ProviderGranite 4 H Small inGranite 4 H Small outQwen2.5 Coder 32B Instruct inQwen2.5 Coder 32B Instruct out
Ibm Watsonx$0.060/M$0.250/M——
Openrouter——$0.180/M$0.180/M

Frequently asked questions

Qwen2.5 Coder 32B Instruct has a larger context window: 33K tokens vs 20K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

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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.

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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