Granite Embedding 278m Multilingual vs GLM 5.3 Flash
At a Glance
| Compare |  GLM 5.3 FlashZ.ai | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #29 of 4654.6 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 36.4–69.8 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #2 of 44$0.0087 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #1 of 3877.3 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 68.2–84.9 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.106IBM watsonx.ai ↗ · Aug 29, 2026 | $0.075Z.ai ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $0.25Z.ai ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 1K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 2, 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-278m-multilingual | GLM-5.3-Flash |
|---|---|---|
| Developer | IBM | Z.ai |
| Family | Granite Embedding 278m Multilingual | Glm 5 3 Flash |
| Model | granite-embedding-278m-multilingual | GLM-5.3-Flash |
| Version | granite-embedding-278m-multilingual | GLM-5.3-Flash |
| Lifecycle | active | active |
| Released | 2024-12-18 | 2026-09-02 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image, Video, Document |
| Output modalities | Embedding | Text |
| Context window | 1K | 1,000K |
| Total parameters | 278M | 320B |
| Active parameters | Unknown | 18B |
| License | apache-2.0 | MIT |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Hugging Face (Standard), IBM watsonx.ai (Pay as you go) | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard) |
| Capabilities | embeddings | agents, chat, computer-use, reasoning, structured_outputs, tools, vision |
Granite Embedding 278m Multilingual Capabilities
GLM 5.3 Flash Capabilities
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Primary Evidence
Sources and Freshness
Questions
Granite Embedding 278m Multilingual vs GLM 5.3 Flash FAQs
Is Granite Embedding 278m Multilingual or GLM 5.3 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Granite Embedding 278m Multilingual and GLM 5.3 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Granite Embedding 278m Multilingual or GLM 5.3 Flash?+
Granite Embedding 278m Multilingual is $0.106 and GLM 5.3 Flash is $0.075 per million tokens, so GLM 5.3 Flash is cheaper on this metric. Only GLM 5.3 Flash has a directly sourced output price: $0.25 per million tokens.
Which has a larger context window, Granite Embedding 278m Multilingual or GLM 5.3 Flash?+
GLM 5.3 Flash has the larger sourced context window. Granite Embedding 278m Multilingual supports 1K and GLM 5.3 Flash supports 1,000K.
Which performs better in benchmarks, Granite Embedding 278m Multilingual or GLM 5.3 Flash?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Granite Embedding 278m Multilingual or GLM 5.3 Flash be self-hosted?+
Both models have the same recorded self-hosting status: supported. Granite Embedding 278m Multilingual is open weight; GLM 5.3 Flash is open weight.
Can Granite Embedding 278m Multilingual and GLM 5.3 Flash understand images?+
Granite Embedding 278m Multilingual is not documented with image input; GLM 5.3 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Granite Embedding 278m Multilingual or GLM 5.3 Flash?+
Neither has a larger sourced maximum output. Granite Embedding 278m Multilingual is — and GLM 5.3 Flash is 131K.
Do Granite Embedding 278m Multilingual and GLM 5.3 Flash support reasoning and tool use?+
Granite Embedding 278m Multilingual: none of these features are definitively sourced. GLM 5.3 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Granite Embedding 278m Multilingual or GLM 5.3 Flash?+
Granite Embedding 278m Multilingual has 2 sourced provider routes; GLM 5.3 Flash has 4, so GLM 5.3 Flash has broader tracked availability.
Which offers better value, Granite Embedding 278m Multilingual or GLM 5.3 Flash?+
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.