Granite Embedding 30m English vs GLM 5.2
At a Glance
| Compare | GLM 5.2Z.ai | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot 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 estimate | UnrankedNot in the 44-model eligible cohort | #12 of 44$0.056 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot 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 tokens | Not reported | $0.75Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $2.40Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1K | 1,049K |
| Model facts checked | Aug 28, 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 | granite-embedding-30m-english | GLM-5.2 |
|---|---|---|
| Developer | IBM | Z.ai |
| Family | Granite Embedding 30m English | Glm 5 2 |
| Model | granite-embedding-30m-english | GLM-5.2 |
| Version | granite-embedding-30m-english | GLM-5.2 |
| Lifecycle | active | active |
| Released | 2025-08-29 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Embedding | Text |
| Context window | 1K | 1,049K |
| Total parameters | 30.3M | 753.3B |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Hugging Face (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | embeddings | chat, generation, reasoning, tools |
Granite Embedding 30m English Capabilities
GLM 5.2 Capabilities
Primary Evidence
Sources and Freshness
Questions
Granite Embedding 30m English vs GLM 5.2 FAQs
Is Granite Embedding 30m English or GLM 5.2 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Granite Embedding 30m English and GLM 5.2, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Granite Embedding 30m English 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, Granite Embedding 30m English or GLM 5.2?+
GLM 5.2 has the larger sourced context window. Granite Embedding 30m English supports 1K and GLM 5.2 supports 1,049K.
Which performs better in benchmarks, Granite Embedding 30m English 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 Granite Embedding 30m English or GLM 5.2 be self-hosted?+
Both models have the same recorded self-hosting status: supported. Granite Embedding 30m English is open weight; GLM 5.2 is open weight.
Can Granite Embedding 30m English and GLM 5.2 understand images?+
Granite Embedding 30m English 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, Granite Embedding 30m English or GLM 5.2?+
Neither has a larger sourced maximum output. Granite Embedding 30m English is — and GLM 5.2 is —.
Do Granite Embedding 30m English and GLM 5.2 support reasoning and tool use?+
Granite Embedding 30m English: 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, Granite Embedding 30m English or GLM 5.2?+
Granite Embedding 30m English has 1 sourced provider route; GLM 5.2 has 5, so GLM 5.2 has broader tracked availability.
Which offers better value, Granite Embedding 30m English 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.