DeepSeek V3.2 Exp is ModelCap archive rank #101 (Measured), from the ModelCap Index as of 22 Sept 2026, 02:49 UTC.
DeepSeek V3.2 Exp listed OpenRouter input price is $0.27 per 1M tokens and listed output price is $0.41 per 1M tokens, from OpenRouter listed prices as of 22 Sept 2026, 02:49 UTC.
DeepSeek V3.2 Exp has a published context limit of 164K tokens in the ModelCap catalogue as of 22 Sept 2026, 02:49 UTC.
DeepSeek V3.2 Exp has 3 published OpenRouter serving endpoints, from OpenRouter as of 22 Sept 2026, 02:49 UTC.
DeepSeek V3.2 Exp weight access is open weights, from ModelCap classification of published repository metadata as of 22 Sept 2026, 02:49 UTC.
Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.
Bayesian Evidence Score · measured evidence input only
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
Observed capability
63.0
Evidence status
confirmed · 76% mass
General preference
63.3
Coding
60.6
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
60%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
16.2
Liquidity (providers × uptime)
98.9
Open reach (HF downloads)
85.4
Surface (context / tools / modalities)
71.8
Freshness
25.6
· OpenRouter popularity #126
· 3 live providers
· HF 30d downloads 50141
· Catalogue: context 163840, reasoning, tools
· First seen 2025-09-29
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
OpenRouter weekly popularity across the full model catalogue.
Liquidity25%
98.9
Independent providers versus the model's open or closed cohort, weighted by uptime.
Open reach15%
85.4
Hugging Face 30-day downloads for open models; neutral for closed models.
Freshness5%
25.6
Time since first public availability, on a six-month half-life.
Specification
Context window
164K tokens
Max output
66K tokens
Inputs
Text
Outputs
Text
Tokenizer
DeepSeek
Cached input tokens
Not offered
First seen on OpenRouter
29 Sept 2025
Knowledge cutoff
2025-07-31
Capabilities
Supported: Reasoning
Supported: Tool use
Supported: Structured output
Supported: Response format
Not supported: Moderated
Weights & access
Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.
DeepSeek V3.2 Exp is a superseded version and is not on the current board as of 22 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
How much does DeepSeek V3.2 Exp cost per 1M tokens?
DeepSeek V3.2 Exp is listed at $0.27 per 1M input tokens and $0.41 per 1M output tokens as of 22 September 2026 across 3 providers. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.745 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
What is the context window of DeepSeek V3.2 Exp?
DeepSeek V3.2 Exp has a published context window of 164K tokens (163,840) and a maximum output of 66K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.
Is DeepSeek V3.2 Exp open-weight?
Open weights (mit). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is deepseek-ai/DeepSeek-V3.2-Exp on Hugging Face.
Which API providers serve DeepSeek V3.2 Exp?
3 providers serve DeepSeek V3.2 Exp through OpenRouter as of 22 September 2026: SiliconFlow, AtlasCloud and Novita. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Which benchmarks has DeepSeek V3.2 Exp been evaluated on?
DeepSeek V3.2 Exp has published results on 2 public boards tracked by ModelCap as of 22 September 2026: Arena coding 1476 (#103 of 397) and BFCL V4 56.7 (#12 of 83). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.
When was DeepSeek V3.2 Exp released?
DeepSeek V3.2 Exp first appeared in the catalogue on 29 Sept 2025, with a published knowledge cutoff of 2025-07-31. It has since been superseded by DeepSeek V3.2. Rank and price movements since then are recorded on the site's changes feed.