Context Window

Compare

Grok 4.20 vs Qwen3 Coder 480b A35b Instruct Fp8

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.

Xai

Model

Grok 4.20

Image inputTool calling

Context window

2M

2,000,000 tokens · ~1.5M words

Model page
Alibaba

Model

Qwen3 Coder 480b A35b Instruct Fp8

Tool calling

Context window

256K

256,000 tokens · ~192K 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.

Grok 4.202M
Qwen3 Coder 480b A35b Instruct Fp8256K

Grok 4.20 has about 7.8× the context window of the other in this pair.

Token calculator →Memory savings →

Grok 4.20 has 681% more context capacity (2000K vs 256K tokens). Grok 4.20 is 37% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Grok 4.20. Its 2000K context fits entire documents without chunking (vs 256K).

  • RAG / high-volume retrieval

    Use Grok 4.20. Input tokens are 37% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecGrok 4.20Qwen3 Coder 480b A35b Instruct Fp8
Context window2,000,000 tokens (2000K)256,000 tokens (256K)
Max output tokens1,800,000 tokens (1800K)N/A
Speed tierBalancedBalanced
VisionYesNo
Function callingYesYes
Extended thinkingYesNo
Prompt cachingYesYes
Batch APINoNo
Release dateMar 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.

ProviderGrok 4.20 inGrok 4.20 outQwen3 Coder 480b A35b Instruct Fp8 inQwen3 Coder 480b A35b Instruct Fp8 out
Gmi——$0.900/M$4.50/M
Openrouter$1.25/M$2.50/M——
Together Ai——$2.00/M$2.00/M
Xai$1.25/M$2.50/M——

Frequently asked questions

Grok 4.20 has a larger context window: 2000K tokens vs 256K. 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