Gemini Deep Research Max vs Codestral 22B v0.1

At a Glance

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Pricing and Limits
Context windowMaximum documented tokens1,049K33K
Model facts checkedAug 29, 2026View model evidence →Aug 28, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldGemini Deep Research MaxCodestral-22B-v0.1
DeveloperGoogle DeepMindMistral AI
FamilyGemini AgentsCodestral 22b V0 1
ModelGemini Deep Research MaxCodestral-22B-v0.1
VersionGemini Deep Research MaxCodestral-22B-v0.1
Lifecyclepreviewactive
ReleasedUnknownUnknown
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, Audio, DocumentText
Output modalitiesText, ImageText
Context window1,049K33K
Total parametersUnknown22.2B
Active parametersUnknownUnknown
LicenseUnknownother
Open weightsNoYes
API availableYesUnknown
Self-hostableNoYes
Provider accessGoogle AI (Standard), Google Gemini (Standard)Unknown
Capabilitiesgeneration, reasoning, research, toolsgeneration

Gemini Deep Research Max Capabilities

generationreasoningresearchtools
Serving providers2
Canonical IDgoogle-deepmind/deep-research-max-preview-04-2026

Codestral 22B v0.1 Capabilities

generation
Serving providers0
Canonical IDmistralai/Codestral-22B-v0.1

Primary Evidence

Sources and Freshness

Questions

Gemini Deep Research Max vs Codestral 22B v0.1 FAQs

Is Gemini Deep Research Max or Codestral 22B v0.1 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini Deep Research Max and Codestral 22B v0.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini Deep Research Max or Codestral 22B v0.1?+

Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.

Which has a larger context window, Gemini Deep Research Max or Codestral 22B v0.1?+

Gemini Deep Research Max has the larger sourced context window. Gemini Deep Research Max supports 1,049K and Codestral 22B v0.1 supports 33K.

Which performs better in benchmarks, Gemini Deep Research Max or Codestral 22B v0.1?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Gemini Deep Research Max or Codestral 22B v0.1 be self-hosted?+

Codestral 22B v0.1 is the only model in this pair currently marked as self-hostable. Gemini Deep Research Max is not marked open weight; Codestral 22B v0.1 is open weight.

Can Gemini Deep Research Max and Codestral 22B v0.1 understand images?+

Gemini Deep Research Max is documented with image input; Codestral 22B v0.1 is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini Deep Research Max or Codestral 22B v0.1?+

Neither has a larger sourced maximum output. Gemini Deep Research Max is 66K and Codestral 22B v0.1 is —.

Do Gemini Deep Research Max and Codestral 22B v0.1 support reasoning and tool use?+

Gemini Deep Research Max: reasoning, tool calling, and image input. Codestral 22B v0.1: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, Gemini Deep Research Max or Codestral 22B v0.1?+

Gemini Deep Research Max has 2 sourced provider routes; Codestral 22B v0.1 has 0, so Gemini Deep Research Max has broader tracked availability.

Which offers better value, Gemini Deep Research Max or Codestral 22B v0.1?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

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