Claude Opus 4.8 vs Muse Spark 1.3

At a Glance

Compare
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5#18 of 4670.1 score · 3/3 sources · completeUnrankedNot in the 46-model eligible cohort
CostLower is better · Published-token output estimate#42 of 44$0.604 per LiveBench caseUnrankedNot in the 44-model eligible cohort
EfficiencyHigher is better · MM Efficiency v1.5#35 of 3840.5 score · 3/3 sources · completeUnrankedNot in the 38-model eligible cohort
Pricing and Limits
Input priceFrom · USD / 1M tokens$5.00Anthropic · Sep 3, 2026Not reported
Output priceFrom · USD / 1M tokens$25.00Anthropic · Sep 3, 2026Not reported
Context windowMaximum documented tokens1,000KNot reported
Model facts checkedAug 29, 2026View model evidence →Sep 4, 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 →
BenchmarkClaude Opus 4.8Muse Spark 1.3
LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader8.19100% of row best · score · Claude Opus 4.8 (High); 95% CI [6.91963673, 9.45737628]; sessions 39731; observations 2097389; rank 64.2096% of row best · score · Muse Spark 1.3 (Max); 95% CI [3.33950614, 5.06185896]; sessions 31052; observations 2525117; rank 15
LMArena Document Arenadocument-2026-09-13-d25aabda0010 · arena_rating · statistical tie1,464.07100% of row best · rating · claude-opus-4-8; 95% CI [1457.10320334, 1471.03216030]; votes 12128; rank 191,470.66100% of row best · rating · muse-spark-1.3-max; 95% CI [1452.36505006, 1488.94793707]; votes 1006; rank 15
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,452.6698% of row best · rating · claude-opus-4-8; 95% CI [1448.52490690, 1456.79817098]; votes 53446; rank 401,489.74100% of row best · rating · muse-spark-1.3-max; 95% CI [1480.91456937, 1498.56660928]; votes 4723; rank 10
LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader1,288.2398% of row best · rating · claude-opus-4-8; 95% CI [1281.27991800, 1295.18871241]; votes 15801; rank 251,314.56100% of row best · rating · muse-spark-1.3-max; 95% CI [1299.74034111, 1329.38210317]; votes 1804; rank 8
LiveBench2026-06-25 · overall · leader81.1895% of row best · percent · claude-opus-4-8-max-effort · 24,171 output tokens / case85.47100% of row best · percent · muse-spark-1.3-xhigh · 28,234 output tokens / case
ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified87.91100% of row best · points · Claude Opus 4.8 (max effort) · 24,846 output tokens / case82.6394% of row best · points · Muse Spark 1.3 (thinking) · 6,301 output tokens / case
Overall ResultCounted from the protocol-matched rows above · 1 tie1 benchmark win3 benchmark winsOverall lead

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

Side-by-Side Facts

FieldClaude Opus 4.8Muse Spark 1.3
DeveloperAnthropicMeta
FamilyClaude 4 8Muse Spark
ModelClaude Opus 4.8Muse Spark 1.3
VersionClaude Opus 4.8Muse Spark 1.3
Lifecycleactivepreview
Released2026-05-282026-09-02
Knowledge cutoff2026-01-01Unknown
Input modalitiesText, ImageText, Image, Video
Output modalitiesTextText
Context window1,000KUnknown
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessAnthropic (Standard), Deepinfra (Standard)Unknown
Capabilitieschat, generation, reasoning, toolschat, computer-use, generation, reasoning, research, tools

Claude Opus 4.8 Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDanthropic/claude-opus-4-8

Muse Spark 1.3 Capabilities

chatcomputer-usegenerationreasoningresearchtools
Serving providers0
Canonical IDmeta-llama/muse-spark-1.3

Primary Evidence

Sources and Freshness

Questions

Claude Opus 4.8 vs Muse Spark 1.3 FAQs

Is Claude Opus 4.8 or Muse Spark 1.3 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Claude Opus 4.8 and Muse Spark 1.3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Claude Opus 4.8 or Muse Spark 1.3?+

Only Claude Opus 4.8 has a directly sourced input price: $5.00 per million tokens. Only Claude Opus 4.8 has a directly sourced output price: $25.00 per million tokens.

Which has a larger context window, Claude Opus 4.8 or Muse Spark 1.3?+

Neither model has a larger sourced context window in this comparison. Claude Opus 4.8 is 1,000K and Muse Spark 1.3 is —.

Which performs better in benchmarks, Claude Opus 4.8 or Muse Spark 1.3?+

Muse Spark 1.3 leads the current overall benchmark count. The result uses 5 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.

Can Claude Opus 4.8 or Muse Spark 1.3 be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Claude Opus 4.8 is not marked open weight; Muse Spark 1.3 is not marked open weight.

Can Claude Opus 4.8 and Muse Spark 1.3 understand images?+

Claude Opus 4.8 is documented with image input; Muse Spark 1.3 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Claude Opus 4.8 or Muse Spark 1.3?+

Neither has a larger sourced maximum output. Claude Opus 4.8 is 128K and Muse Spark 1.3 is —.

Do Claude Opus 4.8 and Muse Spark 1.3 support reasoning and tool use?+

Claude Opus 4.8: reasoning, tool calling, and image input. Muse Spark 1.3: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Claude Opus 4.8 or Muse Spark 1.3?+

Claude Opus 4.8 has 2 sourced provider routes; Muse Spark 1.3 has 0, so Claude Opus 4.8 has broader tracked availability.

Which offers better value, Claude Opus 4.8 or Muse Spark 1.3?+

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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