Gemini Deep Research Max vs Muse Spark 1.1

At a Glance

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Pricing and Limits
Context windowMaximum documented tokens1,049K1,000K
Model facts checkedAug 29, 2026View model evidence →Sep 3, 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 MaxMuse Spark 1.1
DeveloperGoogle DeepMindMeta
FamilyGemini AgentsMuse Spark
ModelGemini Deep Research MaxMuse Spark 1.1
VersionGemini Deep Research MaxMuse Spark 1.1
Lifecyclepreviewpreview
ReleasedUnknown2026-07-09
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, Audio, DocumentText, Image, Video, Audio
Output modalitiesText, ImageText
Context window1,049K1,000K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessGoogle AI (Standard), Google Gemini (Standard)Unknown
Capabilitiesgeneration, reasoning, research, toolschat, computer-use, generation, reasoning, research, structured_outputs, tools

Gemini Deep Research Max Capabilities

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

Muse Spark 1.1 Capabilities

chatcomputer-usegenerationreasoningresearchstructured outputstools
Serving providers0
Canonical IDmeta-llama/muse-spark-1.1

Primary Evidence

Sources and Freshness

Questions

Gemini Deep Research Max vs Muse Spark 1.1 FAQs

Is Gemini Deep Research Max or Muse Spark 1.1 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Gemini Deep Research Max and Muse Spark 1.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Gemini Deep Research Max or Muse Spark 1.1?+

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 Muse Spark 1.1?+

Gemini Deep Research Max has the larger sourced context window. Gemini Deep Research Max supports 1,049K and Muse Spark 1.1 supports 1,000K.

Which performs better in benchmarks, Gemini Deep Research Max or Muse Spark 1.1?+

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 Muse Spark 1.1 be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Gemini Deep Research Max is not marked open weight; Muse Spark 1.1 is not marked open weight.

Can Gemini Deep Research Max and Muse Spark 1.1 understand images?+

Gemini Deep Research Max is documented with image input; Muse Spark 1.1 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Gemini Deep Research Max or Muse Spark 1.1?+

Neither has a larger sourced maximum output. Gemini Deep Research Max is 66K and Muse Spark 1.1 is —.

Do Gemini Deep Research Max and Muse Spark 1.1 support reasoning and tool use?+

Gemini Deep Research Max: reasoning, tool calling, and image input. Muse Spark 1.1: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Gemini Deep Research Max or Muse Spark 1.1?+

Gemini Deep Research Max has 2 sourced provider routes; Muse Spark 1.1 has 0, so Gemini Deep Research Max has broader tracked availability.

Which offers better value, Gemini Deep Research Max or Muse Spark 1.1?+

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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