DeepSeek V3 vs Granite Embedding English r2

At a Glance

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DeepSeek V3DeepSeek
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.2574Openrouter · Aug 29, 2026Not reported
Output priceFrom · USD / 1M tokens$0.89Deepinfra · Sep 23, 2026Not reported
Context windowMaximum documented tokens164K8K
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

FieldDeepSeek-V3granite-embedding-english-r2
DeveloperDeepSeekIBM
FamilyDeepseek V3Granite Embedding English R2
ModelDeepSeek-V3granite-embedding-english-r2
VersionDeepSeek-V3granite-embedding-english-r2
Lifecycleactiveactive
Released2024-12-262025-08-15
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextEmbedding
Context window164K8K
Total parameters684.5B149M
Active parameters37BUnknown
LicenseUnknownapache-2.0
Open weightsYesYes
API availableYesUnknown
Self-hostableYesYes
Provider accessDeepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)Unknown
Capabilitieschat, generationembeddings

DeepSeek V3 Capabilities

chatgeneration
Serving providers3
Canonical IDdeepseek-ai/DeepSeek-V3

Granite Embedding English r2 Capabilities

embeddings
Serving providers0
Canonical IDibm-granite/granite-embedding-english-r2

Primary Evidence

Sources and Freshness

Questions

DeepSeek V3 vs Granite Embedding English r2 FAQs

Is DeepSeek V3 or Granite Embedding English r2 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V3 and Granite Embedding English r2, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, DeepSeek V3 or Granite Embedding English r2?+

Only DeepSeek V3 has a directly sourced input price: $0.2574 per million tokens. Only DeepSeek V3 has a directly sourced output price: $0.89 per million tokens.

Which has a larger context window, DeepSeek V3 or Granite Embedding English r2?+

DeepSeek V3 has the larger sourced context window. DeepSeek V3 supports 164K and Granite Embedding English r2 supports 8K.

Which performs better in benchmarks, DeepSeek V3 or Granite Embedding English r2?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can DeepSeek V3 or Granite Embedding English r2 be self-hosted?+

Both models have the same recorded self-hosting status: supported. DeepSeek V3 is open weight; Granite Embedding English r2 is open weight.

Can DeepSeek V3 and Granite Embedding English r2 understand images?+

DeepSeek V3 is not documented with image input; Granite Embedding English r2 is not documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, DeepSeek V3 or Granite Embedding English r2?+

Neither has a larger sourced maximum output. DeepSeek V3 is — and Granite Embedding English r2 is —.

Do DeepSeek V3 and Granite Embedding English r2 support reasoning and tool use?+

DeepSeek V3: none of these features are definitively sourced. Granite Embedding English r2: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, DeepSeek V3 or Granite Embedding English r2?+

DeepSeek V3 has 3 sourced provider routes; Granite Embedding English r2 has 0, so DeepSeek V3 has broader tracked availability.

Which offers better value, DeepSeek V3 or Granite Embedding English r2?+

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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