Muse Spark 1.2 vs phi-4

At a Glance

Compare
phi-4Microsoft
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.070Deepinfra · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$0.14Deepinfra · Sep 22, 2026
Context windowMaximum documented tokensNot reported16K
Model facts checkedSep 3, 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 1.2phi-4
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,489.44100% of row best · rating · muse-spark-1.2 (xHigh); 95% CI [1478.95697715, 1499.92080617]; votes 3227; rank 111,216.6082% of row best · rating · phi-4; 95% CI [1212.02298793, 1221.18318193]; votes 24126; rank 300
Overall ResultCounted from the protocol-matched rows above1 benchmark winNo overall winner0 benchmark winsNo overall winner

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 1.2phi-4
DeveloperMetaMicrosoft
FamilyMuse SparkPhi 4
ModelMuse Spark 1.2phi-4
VersionMuse Spark 1.2phi-4
Lifecyclepreviewactive
Released2026-08-052024-12-12
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, Video, AudioText
Output modalitiesTextText
Context windowUnknown16K
Total parametersUnknown14.7B
Active parametersUnknownUnknown
LicenseUnknownmit
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessUnknownDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)
Capabilitieschat, computer-use, generation, reasoning, research, structured_outputs, toolschat, generation

Muse Spark 1.2 Capabilities

chatcomputer-usegenerationreasoningresearchstructured outputstools
Serving providers0
Canonical IDmeta-llama/muse-spark-1.2

phi-4 Capabilities

chatgeneration
Serving providers3
Canonical IDmicrosoft/phi-4

Primary Evidence

Sources and Freshness

Questions

Muse Spark 1.2 vs phi-4 FAQs

Is Muse Spark 1.2 or phi-4 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Muse Spark 1.2 and phi-4, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Muse Spark 1.2 or phi-4?+

Only phi-4 has a directly sourced input price: $0.070 per million tokens. Only phi-4 has a directly sourced output price: $0.14 per million tokens.

Which has a larger context window, Muse Spark 1.2 or phi-4?+

Neither model has a larger sourced context window in this comparison. Muse Spark 1.2 is — and phi-4 is 16K.

Which performs better in benchmarks, Muse Spark 1.2 or phi-4?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Muse Spark 1.2 or phi-4 be self-hosted?+

phi-4 is the only model in this pair currently marked as self-hostable. Muse Spark 1.2 is not marked open weight; phi-4 is open weight.

Can Muse Spark 1.2 and phi-4 understand images?+

Muse Spark 1.2 is documented with image input; phi-4 is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Muse Spark 1.2 or phi-4?+

Neither has a larger sourced maximum output. Muse Spark 1.2 is — and phi-4 is —.

Do Muse Spark 1.2 and phi-4 support reasoning and tool use?+

Muse Spark 1.2: reasoning, tool calling, and image input. phi-4: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, Muse Spark 1.2 or phi-4?+

Muse Spark 1.2 has 0 sourced provider routes; phi-4 has 3, so phi-4 has broader tracked availability.

Which offers better value, Muse Spark 1.2 or phi-4?+

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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