Granite 4.2 30B vs Muse Spark 1.1

Benchmark Performance

Available Benchmarks

BenchmarkGranite 4.2 30BMuse Spark 1.1
LMArena Text Arenatext-2026-09-01-011508720696 · arena_rating · leader1,362.5592% of row best · rating · granite-4.2-30b; 95% CI [1351.93384890, 1373.17607017]; votes 3287; rank 1771,479.03100% of row best · rating · muse-spark-1.1; 95% CI [1473.99485495, 1484.06002682]; votes 23768; rank 14
Overall ResultCounted from the protocol-matched rows above0 benchmark wins1 benchmark winOverall lead

Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.

FieldAt a Glance
IBM · activeGranite 4.2 30BVerified Sep 2, 2026
Meta · previewMuse Spark 1.1Verified Sep 3, 2026

Technical Differences

Side-by-Side Facts

Indexable
FieldGranite 4.2 30BMuse Spark 1.1
DeveloperIBMMeta
FamilyGranite 4 2Muse Spark
ModelGranite 4.2 30BMuse Spark 1.1
VersionGranite 4.2 30BMuse Spark 1.1
Lifecycleactivepreview
Released2026-08-252026-07-09
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Video, Audio
Output modalitiesTextText
Context window131K1,000K
Total parameters29.3BUnknown
Active parametersUnknownUnknown
Licenseapache-2.0Unknown
Open weightsYesNo
API availableYesYes
Self-hostableYesNo
Provider accessDeepinfra (Standard)Unknown
Capabilitieschat, generation, reasoning, structured_outputs, toolschat, computer-use, generation, reasoning, research, structured_outputs, tools

13 comparable fields · 11 material differences · Pair passes the primary-source comparison gate

Granite 4.2 30B Capabilities

chatgenerationreasoningstructured outputstools
Input price$0.16
Output price$0.65
Serving providers1
Canonical IDibm-granite/granite-4.2-30b

Muse Spark 1.1 Capabilities

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

Internal Comparison Graph

Related Comparisons

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Primary Evidence

Sources and Freshness

Questions

Granite 4.2 30B vs Muse Spark 1.1 FAQs

Is Granite 4.2 30B or Muse Spark 1.1 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Granite 4.2 30B and Muse Spark 1.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Granite 4.2 30B or Muse Spark 1.1?+

Only Granite 4.2 30B has a directly sourced input price: $0.16 per million tokens. Only Granite 4.2 30B has a directly sourced output price: $0.65 per million tokens.

Which has a larger context window, Granite 4.2 30B or Muse Spark 1.1?+

Muse Spark 1.1 has the larger sourced context window. Granite 4.2 30B supports 131K and Muse Spark 1.1 supports 1,000K.

Which performs better in benchmarks, Granite 4.2 30B 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 Granite 4.2 30B or Muse Spark 1.1 be self-hosted?+

Granite 4.2 30B is the only model in this pair currently marked as self-hostable. Granite 4.2 30B is open weight; Muse Spark 1.1 is not marked open weight.

Can Granite 4.2 30B and Muse Spark 1.1 understand images?+

Granite 4.2 30B is not 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, Granite 4.2 30B or Muse Spark 1.1?+

Neither has a larger sourced maximum output. Granite 4.2 30B is — and Muse Spark 1.1 is —.

Do Granite 4.2 30B and Muse Spark 1.1 support reasoning and tool use?+

Granite 4.2 30B: reasoning and tool calling. Muse Spark 1.1: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Granite 4.2 30B or Muse Spark 1.1?+

Granite 4.2 30B has 1 sourced provider route; Muse Spark 1.1 has 0, so Granite 4.2 30B has broader tracked availability.

Which offers better value, Granite 4.2 30B 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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