Muse Spark 1.3 vs GPT-5.6 Terra

At a Glance

Compare
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5UnrankedNot in the 46-model eligible cohort#13 of 4674.9 score · 3/3 sources · complete
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#35 of 44$0.266 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5UnrankedNot in the 38-model eligible cohort#23 of 3851.5 score · 3/3 sources · complete
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$2.00Openai · Sep 3, 2026
Output priceFrom · USD / 1M tokensNot reported$12.00Openai · Sep 3, 2026
Context windowMaximum documented tokensNot reported1,050K
Model facts checkedSep 4, 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 →
BenchmarkMuse Spark 1.3GPT-5.6 Terra
LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader4.20100% of row best · score · Muse Spark 1.3 (Max); 95% CI [3.33950614, 5.06185896]; sessions 31052; observations 2525117; rank 151.4497% of row best · score · GPT 5.6 Terra (xHigh); 95% CI [0.32735411, 2.55262103]; sessions 20301; observations 1231027; rank 23
LMArena Document Arenadocument-2026-09-13-d25aabda0010 · arena_rating · statistical tie1,470.66100% of row best · rating · muse-spark-1.3-max; 95% CI [1452.36505006, 1488.94793707]; votes 1006; rank 151,471.58100% of row best · rating · gpt-5.6-terra-xhigh; 95% CI [1463.31179298, 1479.85049651]; votes 5787; rank 13
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,489.74100% of row best · rating · muse-spark-1.3-max; 95% CI [1480.91456937, 1498.56660928]; votes 4723; rank 101,446.2297% of row best · rating · gpt-5.6-terra-xhigh; 95% CI [1441.41414497, 1451.02563541]; votes 28119; rank 52
LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader1,314.56100% of row best · rating · muse-spark-1.3-max; 95% CI [1299.74034111, 1329.38210317]; votes 1804; rank 81,269.9097% of row best · rating · gpt-5.6-terra-xhigh; 95% CI [1261.54272100, 1278.25950723]; votes 7726; rank 36
LiveBench2026-06-25 · overall · leader85.47100% of row best · percent · muse-spark-1.3-xhigh · 28,234 output tokens / case82.3196% of row best · percent · gpt-5.6-terra-max · 22,145 output tokens / case
ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified82.6396% of row best · points · Muse Spark 1.3 (thinking) · 6,301 output tokens / case86.39100% of row best · points · GPT-5.6 Terra (ultra) · 11,336 output tokens / case
Overall ResultCounted from the protocol-matched rows above · 1 tie4 benchmark winsOverall lead0 benchmark wins

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

FieldMuse Spark 1.3GPT-5.6 Terra
DeveloperMetaOpenAI
FamilyMuse SparkGpt 5 6
ModelMuse Spark 1.3GPT-5.6 Terra
VersionMuse Spark 1.3GPT-5.6 Terra
Lifecyclepreviewactive
Released2026-09-02Unknown
Knowledge cutoffUnknown2026-02-16
Input modalitiesText, Image, VideoText, Image
Output modalitiesTextText
Context windowUnknown1,050K
Total parametersUnknownUnknown
Active parametersUnknownUnknown
LicenseUnknownUnknown
Open weightsNoNo
API availableYesYes
Self-hostableNoNo
Provider accessUnknownOpenai (Standard), Openrouter (Standard)
Capabilitieschat, computer-use, generation, reasoning, research, toolschat, generation, reasoning, tools

Muse Spark 1.3 Capabilities

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

GPT-5.6 Terra Capabilities

chatgenerationreasoningtools
Serving providers2
Canonical IDopenai/gpt-5.6-terra

Primary Evidence

Sources and Freshness

Questions

Muse Spark 1.3 vs GPT-5.6 Terra FAQs

Is Muse Spark 1.3 or GPT-5.6 Terra better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Muse Spark 1.3 and GPT-5.6 Terra, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Muse Spark 1.3 or GPT-5.6 Terra?+

Only GPT-5.6 Terra has a directly sourced input price: $2.00 per million tokens. Only GPT-5.6 Terra has a directly sourced output price: $12.00 per million tokens.

Which has a larger context window, Muse Spark 1.3 or GPT-5.6 Terra?+

Neither model has a larger sourced context window in this comparison. Muse Spark 1.3 is — and GPT-5.6 Terra is 1,050K.

Which performs better in benchmarks, Muse Spark 1.3 or GPT-5.6 Terra?+

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 Muse Spark 1.3 or GPT-5.6 Terra be self-hosted?+

Both models have the same recorded self-hosting status: unsupported. Muse Spark 1.3 is not marked open weight; GPT-5.6 Terra is not marked open weight.

Can Muse Spark 1.3 and GPT-5.6 Terra understand images?+

Muse Spark 1.3 is documented with image input; GPT-5.6 Terra is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Muse Spark 1.3 or GPT-5.6 Terra?+

Neither has a larger sourced maximum output. Muse Spark 1.3 is — and GPT-5.6 Terra is 128K.

Do Muse Spark 1.3 and GPT-5.6 Terra support reasoning and tool use?+

Muse Spark 1.3: reasoning, tool calling, and image input. GPT-5.6 Terra: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Muse Spark 1.3 or GPT-5.6 Terra?+

Muse Spark 1.3 has 0 sourced provider routes; GPT-5.6 Terra has 2, so GPT-5.6 Terra has broader tracked availability.

Which offers better value, Muse Spark 1.3 or GPT-5.6 Terra?+

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.

Send Feedback