Gemini Deep Research Max vs Granite 4.1 8B

At a Glance

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Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.050Openrouter · Sep 4, 2026
Output priceFrom · USD / 1M tokensNot reported$0.10Openrouter · Sep 4, 2026
Context windowMaximum documented tokens1,049K131K
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 Maxgranite-4.1-8b
DeveloperGoogle DeepMindIBM
FamilyGemini AgentsGranite 4 1 8b
ModelGemini Deep Research Maxgranite-4.1-8b
VersionGemini Deep Research Maxgranite-4.1-8b
Lifecyclepreviewactive
ReleasedUnknown2026-04-29
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, Audio, DocumentText
Output modalitiesText, ImageText
Context window1,049K131K
Total parametersUnknown8.8B
Active parametersUnknownUnknown
LicenseUnknownapache-2.0
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessGoogle AI (Standard), Google Gemini (Standard)Openrouter (Standard)
Capabilitiesgeneration, reasoning, research, toolschat, generation, tools

Gemini Deep Research Max Capabilities

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

Granite 4.1 8B Capabilities

chatgenerationtools
Serving providers1
Canonical IDibm-granite/granite-4.1-8b

Primary Evidence

Sources and Freshness

Questions

Gemini Deep Research Max vs Granite 4.1 8B FAQs

Is Gemini Deep Research Max or Granite 4.1 8B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini Deep Research Max and Granite 4.1 8B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini Deep Research Max or Granite 4.1 8B?+

Only Granite 4.1 8B has a directly sourced input price: $0.050 per million tokens. Only Granite 4.1 8B has a directly sourced output price: $0.10 per million tokens.

Which has a larger context window, Gemini Deep Research Max or Granite 4.1 8B?+

Gemini Deep Research Max has the larger sourced context window. Gemini Deep Research Max supports 1,049K and Granite 4.1 8B supports 131K.

Which performs better in benchmarks, Gemini Deep Research Max or Granite 4.1 8B?+

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 Granite 4.1 8B be self-hosted?+

Granite 4.1 8B is the only model in this pair currently marked as self-hostable. Gemini Deep Research Max is not marked open weight; Granite 4.1 8B is open weight.

Can Gemini Deep Research Max and Granite 4.1 8B understand images?+

Gemini Deep Research Max is documented with image input; Granite 4.1 8B is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini Deep Research Max or Granite 4.1 8B?+

Neither has a larger sourced maximum output. Gemini Deep Research Max is 66K and Granite 4.1 8B is —.

Do Gemini Deep Research Max and Granite 4.1 8B support reasoning and tool use?+

Gemini Deep Research Max: reasoning, tool calling, and image input. Granite 4.1 8B: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Gemini Deep Research Max or Granite 4.1 8B?+

Gemini Deep Research Max has 2 sourced provider routes; Granite 4.1 8B has 1, so Gemini Deep Research Max has broader tracked availability.

Which offers better value, Gemini Deep Research Max or Granite 4.1 8B?+

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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