Granite Embedding 107m Multilingual vs GLM 5.3
At a Glance
| Compare |  GLM 5.3Z.ai | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #16 of 4670.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 46.9–80.3 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #34 of 44$0.248 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #26 of 3850.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 38.2–54.9 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $1.20Deepinfra ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $4.00Deepinfra ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 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-107m-multilingual | GLM-5.3 |
|---|---|---|
| Developer | IBM | Z.ai |
| Family | Granite Embedding 107m Multilingual | Glm 5 3 |
| Model | granite-embedding-107m-multilingual | GLM-5.3 |
| Version | granite-embedding-107m-multilingual | GLM-5.3 |
| Lifecycle | active | active |
| Released | 2024-12-18 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Embedding | Text |
| Context window | 1K | 1,000K |
| Total parameters | 107M | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | Yes | Yes |
| Self-hostable | Yes | No |
| Provider access | Hugging Face (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard) |
| Capabilities | embeddings | agents, chat, reasoning, structured_outputs, tools |
Granite Embedding 107m Multilingual Capabilities
GLM 5.3 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Granite Embedding 107m Multilingual vs GLM 5.3 FAQs
Is Granite Embedding 107m Multilingual or GLM 5.3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Granite Embedding 107m Multilingual and GLM 5.3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Granite Embedding 107m Multilingual or GLM 5.3?+
Only GLM 5.3 has a directly sourced input price: $1.20 per million tokens. Only GLM 5.3 has a directly sourced output price: $4.00 per million tokens.
Which has a larger context window, Granite Embedding 107m Multilingual or GLM 5.3?+
GLM 5.3 has the larger sourced context window. Granite Embedding 107m Multilingual supports 1K and GLM 5.3 supports 1,000K.
Which performs better in benchmarks, Granite Embedding 107m Multilingual or GLM 5.3?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Granite Embedding 107m Multilingual or GLM 5.3 be self-hosted?+
Granite Embedding 107m Multilingual is the only model in this pair currently marked as self-hostable. Granite Embedding 107m Multilingual is open weight; GLM 5.3 is not marked open weight.
Can Granite Embedding 107m Multilingual and GLM 5.3 understand images?+
Granite Embedding 107m Multilingual is not documented with image input; GLM 5.3 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Granite Embedding 107m Multilingual or GLM 5.3?+
Neither has a larger sourced maximum output. Granite Embedding 107m Multilingual is — and GLM 5.3 is 131K.
Do Granite Embedding 107m Multilingual and GLM 5.3 support reasoning and tool use?+
Granite Embedding 107m Multilingual: none of these features are definitively sourced. GLM 5.3: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Granite Embedding 107m Multilingual or GLM 5.3?+
Granite Embedding 107m Multilingual has 1 sourced provider route; GLM 5.3 has 4, so GLM 5.3 has broader tracked availability.
Which offers better value, Granite Embedding 107m Multilingual or GLM 5.3?+
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.