Context Window

Compare

GPT-6.1 Sol vs Mixtral 8x22b Instruct V0 1

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.

Openai

Model

GPT-6.1 Sol

Image inputTool calling

Context window

922K

922,000 tokens · ~692K words

Model page
Mistral

Model

Mixtral 8x22b Instruct V0 1

Tool calling

Context window

66K

65,536 tokens · ~49K 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.

GPT-6.1 Sol922K
Mixtral 8x22b Instruct V0 166K

GPT-6.1 Sol has about 14.1× the context window of the other in this pair.

Token calculator →Memory savings →

GPT-6.1 Sol has 1306% more context capacity (922K vs 65K tokens). Mixtral 8x22b Instruct V0 1 is 70% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use GPT-6.1 Sol. Its 922K context fits entire documents without chunking (vs 65K).

  • RAG / high-volume retrieval

    Use Mixtral 8x22b Instruct V0 1. Input tokens are 70% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use GPT-6.1 Sol. Its 128K 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.

SpecGPT-6.1 SolMixtral 8x22b Instruct V0 1
Context window922,000 tokens (922K)65,536 tokens (65K)
Max output tokens128,000 tokens (128K)65,536 tokens (65K)
Speed tierBalancedBalanced
VisionYesNo
Function callingYesYes
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateSep 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.

ProviderGPT-6.1 Sol inGPT-6.1 Sol outMixtral 8x22b Instruct V0 1 inMixtral 8x22b Instruct V0 1 out
Anyscale——$0.900/M$0.900/M
Azure$2.00/M$10.00/M——
Nscale——$0.600/M$0.600/M
Openai$2.00/M$10.00/M——
Openrouter$2.00/M$10.00/M——

Frequently asked questions

GPT-6.1 Sol has a larger context window: 922K tokens vs 65K. 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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Use a smaller model.
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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