SOMA X v0.3.0 vs GLM 5.2

At a Glance

Compare
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v2.5UnrankedNot in the 46-model eligible cohort#23 of 4661.9 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 41.3–74.6
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#12 of 44$0.056 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.5UnrankedNot in the 38-model eligible cohort#7 of 3861.3 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 51.0–67.6
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.75Deepinfra · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$2.40Deepinfra · Sep 22, 2026
Context windowMaximum documented tokensNot reported1,049K
Model facts checkedSep 2, 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 →

Different Model RolesThese models do not share a sourced market category. Their primary-source facts remain comparable below, while performance claims require matched evidence.

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

FieldSOMA-X v0.3.0GLM-5.2
DeveloperNVIDIAZ.ai
FamilySoma XGlm 5 2
ModelSOMA-X v0.3.0GLM-5.2
VersionSOMA-X v0.3.0GLM-5.2
Lifecycleactiveactive
Released2026-09-02Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesModel-specific inputText
Output modalities3DText
Context windowUnknown1,049K
Total parametersUnknown753.3B
Active parametersUnknownUnknown
Licenseapache-2.0mit
Open weightsYesYes
API availableNoYes
Self-hostableYesYes
Provider accessUnknownDeepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitiesanimation, hand-modeling, human-body-modeling, motion-retargeting, pose-inversion, simulationchat, generation, reasoning, tools

SOMA X v0.3.0 Capabilities

animationhand-modelinghuman-body-modelingmotion-retargetingpose-inversionsimulation
Serving providers0
Canonical IDnvidia/SOMA-X-v0.3.0

GLM 5.2 Capabilities

chatgenerationreasoningtools
Serving providers5
Canonical IDzai-org/GLM-5.2

Primary Evidence

Sources and Freshness

Questions

SOMA X v0.3.0 vs GLM 5.2 FAQs

Is SOMA X v0.3.0 or GLM 5.2 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both SOMA X v0.3.0 and GLM 5.2, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, SOMA X v0.3.0 or GLM 5.2?+

Only GLM 5.2 has a directly sourced input price: $0.75 per million tokens. Only GLM 5.2 has a directly sourced output price: $2.40 per million tokens.

Which has a larger context window, SOMA X v0.3.0 or GLM 5.2?+

Neither model has a larger sourced context window in this comparison. SOMA X v0.3.0 is — and GLM 5.2 is 1,049K.

Which performs better in benchmarks, SOMA X v0.3.0 or GLM 5.2?+

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

Can SOMA X v0.3.0 or GLM 5.2 be self-hosted?+

Both models have the same recorded self-hosting status: supported. SOMA X v0.3.0 is open weight; GLM 5.2 is open weight.

Can SOMA X v0.3.0 and GLM 5.2 understand images?+

SOMA X v0.3.0 is not documented with image input; GLM 5.2 is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, SOMA X v0.3.0 or GLM 5.2?+

Neither has a larger sourced maximum output. SOMA X v0.3.0 is — and GLM 5.2 is —.

Do SOMA X v0.3.0 and GLM 5.2 support reasoning and tool use?+

SOMA X v0.3.0: none of these features are definitively sourced. GLM 5.2: reasoning and tool calling. Feature support does not establish relative quality.

Which is available from more inference providers, SOMA X v0.3.0 or GLM 5.2?+

SOMA X v0.3.0 has 0 sourced provider routes; GLM 5.2 has 5, so GLM 5.2 has broader tracked availability.

Which offers better value, SOMA X v0.3.0 or GLM 5.2?+

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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