Gemini Deep Research Max vs Llama 3.1 405B Instruct

At a Glance

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Pricing and Limits
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 MaxLlama-3.1-405B-Instruct
DeveloperGoogle DeepMindMeta
FamilyGemini AgentsLlama 3 1 405b Instruct
ModelGemini Deep Research MaxLlama-3.1-405B-Instruct
VersionGemini Deep Research MaxLlama-3.1-405B-Instruct
Lifecyclepreviewactive
ReleasedUnknown2024-07-23
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, Audio, DocumentText
Output modalitiesText, ImageText
Context window1,049K131K
Total parametersUnknown405.9B
Active parametersUnknownUnknown
LicenseUnknownllama3.1
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessGoogle AI (Standard), Google Gemini (Standard)Together Ai (Standard)
Capabilitiesgeneration, reasoning, research, toolschat, generation, tools

Gemini Deep Research Max Capabilities

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

Llama 3.1 405B Instruct Capabilities

chatgenerationtools
Serving providers1
Canonical IDmeta-llama/Llama-3.1-405B-Instruct

Primary Evidence

Sources and Freshness

Questions

Gemini Deep Research Max vs Llama 3.1 405B Instruct FAQs

Is Gemini Deep Research Max or Llama 3.1 405B Instruct better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini Deep Research Max and Llama 3.1 405B Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini Deep Research Max or Llama 3.1 405B Instruct?+

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 Llama 3.1 405B Instruct?+

Gemini Deep Research Max has the larger sourced context window. Gemini Deep Research Max supports 1,049K and Llama 3.1 405B Instruct supports 131K.

Which performs better in benchmarks, Gemini Deep Research Max or Llama 3.1 405B Instruct?+

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 Llama 3.1 405B Instruct be self-hosted?+

Llama 3.1 405B Instruct is the only model in this pair currently marked as self-hostable. Gemini Deep Research Max is not marked open weight; Llama 3.1 405B Instruct is open weight.

Can Gemini Deep Research Max and Llama 3.1 405B Instruct understand images?+

Gemini Deep Research Max is documented with image input; Llama 3.1 405B Instruct is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini Deep Research Max or Llama 3.1 405B Instruct?+

Neither has a larger sourced maximum output. Gemini Deep Research Max is 66K and Llama 3.1 405B Instruct is —.

Do Gemini Deep Research Max and Llama 3.1 405B Instruct support reasoning and tool use?+

Gemini Deep Research Max: reasoning, tool calling, and image input. Llama 3.1 405B Instruct: tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, Gemini Deep Research Max or Llama 3.1 405B Instruct?+

Gemini Deep Research Max has 2 sourced provider routes; Llama 3.1 405B Instruct has 1, so Gemini Deep Research Max has broader tracked availability.

Which offers better value, Gemini Deep Research Max or Llama 3.1 405B Instruct?+

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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