Granite Embedding 107m Multilingual 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 tokens1K1,049K
Model facts checkedAug 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 →

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

Fieldgranite-embedding-107m-multilingualGLM-5.2
DeveloperIBMZ.ai
FamilyGranite Embedding 107m MultilingualGlm 5 2
Modelgranite-embedding-107m-multilingualGLM-5.2
Versiongranite-embedding-107m-multilingualGLM-5.2
Lifecycleactiveactive
Released2024-12-18Unknown
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesEmbeddingText
Context window1K1,049K
Total parameters107M753.3B
Active parametersUnknownUnknown
Licenseapache-2.0mit
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessHugging Face (Standard)Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitiesembeddingschat, generation, reasoning, tools

Granite Embedding 107m Multilingual Capabilities

embeddings
Serving providers1
Canonical IDibm-granite/granite-embedding-107m-multilingual

GLM 5.2 Capabilities

chatgenerationreasoningtools
Serving providers5
Canonical IDzai-org/GLM-5.2

Primary Evidence

Sources and Freshness

Questions

Granite Embedding 107m Multilingual vs GLM 5.2 FAQs

Is Granite Embedding 107m Multilingual or GLM 5.2 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Granite Embedding 107m Multilingual 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 107m Multilingual 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 107m Multilingual or GLM 5.2?+

GLM 5.2 has the larger sourced context window. Granite Embedding 107m Multilingual supports 1K and GLM 5.2 supports 1,049K.

Which performs better in benchmarks, Granite Embedding 107m Multilingual 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 107m Multilingual or GLM 5.2 be self-hosted?+

Both models have the same recorded self-hosting status: supported. Granite Embedding 107m Multilingual is open weight; GLM 5.2 is open weight.

Can Granite Embedding 107m Multilingual and GLM 5.2 understand images?+

Granite Embedding 107m Multilingual 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 107m Multilingual or GLM 5.2?+

Neither has a larger sourced maximum output. Granite Embedding 107m Multilingual is — and GLM 5.2 is —.

Do Granite Embedding 107m Multilingual and GLM 5.2 support reasoning and tool use?+

Granite Embedding 107m Multilingual: 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 107m Multilingual or GLM 5.2?+

Granite Embedding 107m Multilingual has 1 sourced provider route; GLM 5.2 has 5, so GLM 5.2 has broader tracked availability.

Which offers better value, Granite Embedding 107m Multilingual 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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