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Providers / deepseek/deepseek-v3.2

deepseek/deepseek-v3.2 as each provider declares it

5 of the 12 endpoints declare at least one material setting that differs from the official reference. Declared values, not measured behaviour.

Reference. Context 163,840 tokens, from deepseek-ai/DeepSeek-V3.2 config.json at a7e62ac04e (max_position_embeddings). Quantization: FP8 e4m3, 128x128 blocks.

Provider rows: OpenRouter providers page, the endpoint JSON. Read 2026-10-19.

Endpoints

ProviderQuantizationContextMax outputTools / reasoningDiffers from the reference
AtlasCloud
atlas-cloud/fp8
fp8 (official)163,840147,456yes / yesnone declared
Baidu
baidu/fp8
fp8 (official)131,07265,536no / yesdeclares a 131,072-token context; the reference config says 163,840 (80%)declares no tools parameter; the official model supports tool calling
DeepInfra
deepinfra/fp4
fp4 (differs)163,84016,384yes / yesdeclares fp4 weights; the official release is FP8 e4m3, 128x128 blocks
DigitalOcean
digitalocean
none (not declared)163,840147,456no / yesdeclares no tools parameter; the official model supports tool calling
Friendli
friendli
none (not declared)163,840147,456yes / yesnone declared
GMICloud
gmicloud/fp8
fp8 (official)163,840147,456yes / yesnone declared
Google
google-vertex
none (not declared)163,84065,536yes / yesnone declared
Mara
mara
none (not declared)32,7687,168no / yesdeclares a 32,768-token context; the reference config says 163,840 (20%)declares no tools parameter; the official model supports tool callingdeclares at most 7,168 output tokens, which the reasoning tokens also count against
Phala
phala
none (not declared)163,84064,000yes / yesnone declared
SambaNova
sambanova, status -2
none (not declared)32,7687,168no / yesdeclares a 32,768-token context; the reference config says 163,840 (20%)declares no tools parameter; the official model supports tool callingdeclares at most 7,168 output tokens, which the reasoning tokens also count against
SiliconFlow
siliconflow/fp8
fp8 (official)163,840147,456yes / yesnone declared
Venice
venice
none (not declared)160,00032,768yes / yesdeclares a 160,000-token context; the reference config says 163,840 (98%)

Changes since tracking began

None yet. A row is recorded only when a declared value or the reference moves.

How this is read

Once a day the tracker reads OpenRouter's public endpoint list for each model (one row per provider deployment: declared context length, declared maximum output, declared quantization, and the request parameters it accepts) and the official repository's config.json at its head commit. Both reads are anonymous. A new row is recorded only when either moved, so the history below is a list of real changes.

Every value in the tables is what a provider declares to OpenRouter. No request is sent to any model, so nothing here says how an endpoint behaves: one that declares a 131,072-token context may still cut off earlier, and one that declares the official quantization may still serve something else.

A quantization the provider does not declare cannot be compared, and is counted as undisclosed rather than as matching. A quantization of higher precision than the official weights is shown and not counted as a difference.

Material means one of: a declared context under 95% of the reference config, a declared quantization other than the official release, no tools parameter on a model that supports tool calling, no reasoning control on a model that exposes one, or a reasoning model capped under 8,192 output tokens. A context between 95% and 100% of the reference is listed and not counted as material.

Sampling defaults, chat templates and stop tokens are not in the endpoint metadata and are not compared here. Moonshot's K2 Vendor Verifier (github.com/MoonshotAI/K2-Vendor-Verifier) measures tool-call behaviour across providers for Kimi K2 by sending requests; this page does not.

OpenRouter lists only the providers that serve through it. Nothing here ranks providers, and a provider with no listed difference has not been shown to match the reference, only to declare nothing that differs.

All models As markdown Every row as JSON What changed in the models themselves