SOMA X v0.3.0 vs GLM 5.1
At a Glance
| Compare |  SOMA X v0.3.0NVIDIA |  GLM 5.1Z.ai |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $1.05Deepinfra ↗ · Sep 23, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $3.50Deepinfra ↗ · Sep 23, 2026 |
| Context windowMaximum documented tokens | Not reported | 203K |
| Model facts checked | Sep 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 →
Available Benchmarks
Side-by-Side Facts
| Field | SOMA-X v0.3.0 | GLM-5.1 |
|---|---|---|
| Developer | NVIDIA | Z.ai |
| Family | Soma X | Glm 5 1 |
| Model | SOMA-X v0.3.0 | GLM-5.1 |
| Version | SOMA-X v0.3.0 | GLM-5.1 |
| Lifecycle | active | active |
| Released | 2026-09-02 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Model-specific input | Text |
| Output modalities | 3D | Text |
| Context window | Unknown | 203K |
| Total parameters | Unknown | 753.9B |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | mit |
| Open weights | Yes | Yes |
| API available | No | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Unknown | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | animation, hand-modeling, human-body-modeling, motion-retargeting, pose-inversion, simulation | chat, generation, reasoning, tools |
SOMA X v0.3.0 Capabilities
GLM 5.1 Capabilities
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Primary Evidence
Sources and Freshness
Questions
SOMA X v0.3.0 vs GLM 5.1 FAQs
Is SOMA X v0.3.0 or GLM 5.1 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both SOMA X v0.3.0 and GLM 5.1, 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 5.1?+
Only GLM 5.1 has a directly sourced input price: $1.05 per million tokens. Only GLM 5.1 has a directly sourced output price: $3.50 per million tokens.
Which has a larger context window, SOMA X v0.3.0 or GLM 5.1?+
Neither model has a larger sourced context window in this comparison. SOMA X v0.3.0 is — and GLM 5.1 is 203K.
Which performs better in benchmarks, SOMA X v0.3.0 or GLM 5.1?+
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 5.1 be self-hosted?+
Both models have the same recorded self-hosting status: supported. SOMA X v0.3.0 is open weight; GLM 5.1 is open weight.
Can SOMA X v0.3.0 and GLM 5.1 understand images?+
SOMA X v0.3.0 is not documented with image input; GLM 5.1 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 5.1?+
Neither has a larger sourced maximum output. SOMA X v0.3.0 is — and GLM 5.1 is —.
Do SOMA X v0.3.0 and GLM 5.1 support reasoning and tool use?+
SOMA X v0.3.0: none of these features are definitively sourced. GLM 5.1: 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 5.1?+
SOMA X v0.3.0 has 0 sourced provider routes; GLM 5.1 has 4, so GLM 5.1 has broader tracked availability.
Which offers better value, SOMA X v0.3.0 or GLM 5.1?+
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.