DeepSeek V4 Pro 0813 model profile

Evidence snapshot:

DeepSeek V4 Pro 0813 is a DeepSeek model profile with a 1,048,576-token context window. The dated catalog snapshot records text modalities and interfaces for prompt caching, reasoning controls, structured output, text generation, tool calling.

DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.

DeepSeek V4 Pro 0813 is a reference profile: DeepSeek publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

DeepSeek V4 Pro 0813 is an independent knowledge profile. It does not claim that Kendr hosts the model, quote a Kendr customer price, promise API availability, or advertise a Kendr routing receipt.

DeepSeek V4 Pro 0813 accepts text and returns text. The snapshot records prompt caching, reasoning controls, structured output, text generation, and tool calling as capabilities or interfaces.

The dated reference snapshot lists $0.57948 input and $1.73844 output per million tokens. Cached input is $0.019316 per million tokens.

The 2026-09-06 snapshot includes 3 Artificial Analysis indexes and AutoExacto results for 19 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

DeepSeek V4 Pro 0813 ranked #23 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Profile data was reviewed for the 2026-09-06 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.

Profile facts

Profile type
Model research profile
Provider or publisher
DeepSeek
Context window
1,048,576 tokens
Snapshot date
2026-09-06
Knowledge cutoff
Not disclosed
Reference catalog ID
deepseek/deepseek-v4-pro-0813

When to pick DeepSeek V4 Pro 0813

DeepSeek V4 Pro 0813 is a reference profile: DeepSeek publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

Each condition below is derived from this model's own values in the 2026-09-06 snapshot, compared only against models publishing the same field.

  • Reach for it when a whole corpus has to fit in one prompt. The 1.05M-token context window is in the top quarter of the 163 models publishing a limit here, so long documents can go in whole rather than chunked.
  • Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
  • Reach for it when you want to trade depth against cost per call. Reasoning effort is selectable across max, high, low, so one route can serve both cheap and deep work.
  • Look elsewhere when you need to call it through Kendr today. This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.
  • Look elsewhere when the task is hard reasoning. Its 42.1 Artificial Analysis intelligence index is below the median of the 32 models carrying that field. Scores from different suites are not interchangeable, so treat this as one signal rather than a ranking.

Context, modalities, and identity

DeepSeek V4 Pro 0813 accepts text and returns text. The snapshot records prompt caching, reasoning controls, structured output, text generation, and tool calling as capabilities or interfaces.

Provider or publisher
DeepSeek
Context window
1,048,576 tokens
Maximum output
384,000 tokens
Input modalities
text
Output modalities
text
Knowledge cutoff
Not disclosed

Model overview

DeepSeek V4 Pro 0813 is a large-scale mixture-of-experts model from DeepSeek. This is the GA release of DeepSeek V4 Pro.

Reference model ID
deepseek/deepseek-v4-pro-0813
Canonical version
deepseek/deepseek-v4-pro-20260813
Hugging Face ID
deepseek-ai/DeepSeek-V4-Pro-0813

Capabilities and supported controls

Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.

Supported parameters
frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, presence_penalty, reasoning, reasoning_effort, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p
  • prompt caching
  • reasoning controls
  • structured output
  • text generation
  • tool calling

Dated pricing snapshot

The dated reference snapshot lists $0.57948 input and $1.73844 output per million tokens. Cached input is $0.019316 per million tokens.

These are dated third-party reference prices, not Kendr prices or an availability offer. Routes, tiers, caching, region, and provider policy can change the landed price.

Price date
2026-09-06
Input
$0.57948 per 1M tokens
Cached input
$0.019316 per 1M tokens
Output
$1.73844 per 1M tokens

Provider routes, performance, and uptime

The snapshot retains 19 provider endpoints. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.

Active provider endpoints
19
Best p50 latency
0.55 s
Best p50 throughput
76 tok/s
Availability with routing
99.86% over the sampled window
Availability without routing
98.17% over the sampled window
Performance date
2026-09-06
ProviderQuantizationInput / 1MOutput / 1MCache read / 1MContextp50 latencyp50 throughputUptime (1d)
StreamLakeunknown$0.57948 / 1M$1.73844 / 1M$0.019316 / 1M1,024,000 tokens3.77 s44 tok/s99.89%
Alibaba Cloud Int.unknown$0.5808 / 1M$1.7424 / 1M$0.05808 / 1M1,000,000 tokens1.40 s52 tok/s99.85%
DeepSeekunknown$0.66 / 1M$1.98 / 1M$0.022 / 1M1,048,576 tokens1.04 s22 tok/s100.00%
Baidu Qianfanfp8$1.11936 / 1M$3.35808 / 1M$0.111936 / 1M1,048,576 tokens0.83 s60 tok/s99.99%
GMICloudfp8$1.122 / 1M$3.366 / 1M$0.0374 / 1M1,048,575 tokens6.11 s32 tok/s99.94%
DeepInfrafp8$1.3 / 1M$2.6 / 1M$0.1 / 1M1,048,576 tokens0.80 s59 tok/s99.38%
CoreWeavefp8$1.31 / 1M$3.96 / 1M$0.044 / 1M1,048,576 tokens0.87 s76 tok/s99.90%
NextBitfp8$1.32 / 1M$3.96 / 1M$0.045 / 1M1,048,576 tokens3.41 s40 tok/s99.86%
Sail Researchfp4$1.32 / 1M$3.96 / 1M$0.044 / 1M1,048,576 tokens1.90 s27 tok/s99.95%
Baseten (US)fp4$1.32 / 1M$3.96 / 1M$0.132 / 1M1,048,576 tokens0.62 s41 tok/s99.92%
Parasailfp8$1.32 / 1M$3.96 / 1M$0.044 / 1M1,048,576 tokens1.07 s51 tok/s99.73%
Togetherunknown$1.32 / 1M$3.96 / 1M$0.13 / 1M1,048,576 tokens0.93 s63 tok/s99.72%
DigitalOceanunknown$1.32 / 1M$3.96 / 1M$0.044 / 1M1,048,576 tokens0.80 s52 tok/s99.59%
NovitaAIfp8$1.32 / 1M$3.96 / 1M$0.132 / 1M1,048,576 tokens1.17 s53 tok/s99.99%
SiliconFlowfp8$1.32 / 1M$3.96 / 1M$0.044 / 1M1,048,576 tokens1.44 s51 tok/s99.86%
Basetenfp4$1.32 / 1M$3.96 / 1M$0.132 / 1M1,048,576 tokens0.55 s34 tok/s99.76%
Cloudflareunknown$1.32 / 1M$3.96 / 1M$0.044 / 1M1,048,576 tokens2.33 s51 tok/s99.50%
Fireworksunknown$1.32 / 1M$3.96 / 1M$0.044 / 1M1,048,576 tokens1.60 s62 tok/s99.74%
Phalaunknown$1.45 / 1M$4.36 / 1M$0.15 / 1M1,048,576 tokens1.31 s59 tok/s99.97%

Benchmark evidence and limitations

The 2026-09-06 snapshot includes 3 Artificial Analysis indexes and AutoExacto results for 19 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable.

Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Intelligence Index
42.1
Coding Index
68.8
Agentic Index
42.5
AutoExacto coverage
19 provider observations over 32 days

AutoExacto provider benchmarks

Rolling provider observations from the cited third-party benchmark view. The lookback is 32 days; GPQA Diamond and TAU-Bench Airline measure different abilities and should not be blended into one score.

ProviderGPQA DiamondTAU-Bench AirlineRuns
Alibaba Cloud Int.89.78%77.19%4
auto-routing89.33%77.79%4
Baidu Qianfan91.08%2
Baseten88.21%5
Baseten90.88%74.67%2
Cloudflare87.29%76.28%5
CoreWeave87.68%76%3
DeepInfra78.72%81.33%3
DigitalOcean81.59%67.42%4
Fireworks87.76%3
GMICloud85.45%76.48%5
NextBit92.14%72.67%2
NovitaAI88.53%5
Parasail88.3%76.36%4
Phala88.15%77.55%4
Sail Research87.72%72%4
SiliconFlow89.8%79.86%5
StreamLake88.73%76.8%4
Together87.48%73.27%4

Popularity and market context

DeepSeek V4 Pro 0813 ranked #23 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Third-party catalog rank
#23
Global market share
Not inferred
Observation date
2026-09-06

Frequently asked questions

When should I use DeepSeek V4 Pro 0813?

DeepSeek V4 Pro 0813 is a reference profile: DeepSeek publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call. Reach for it when a whole corpus has to fit in one prompt: The 1.05M-token context window is in the top quarter of the 163 models publishing a limit here, so long documents can go in whole rather than chunked. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose. Reach for it when you want to trade depth against cost per call: Reasoning effort is selectable across max, high, low, so one route can serve both cheap and deep work. Look elsewhere when you need to call it through Kendr today: This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr. Look elsewhere when the task is hard reasoning: Its 42.1 Artificial Analysis intelligence index is below the median of the 32 models carrying that field. Scores from different suites are not interchangeable, so treat this as one signal rather than a ranking.

What is DeepSeek V4 Pro 0813?

DeepSeek V4 Pro 0813 is a DeepSeek model profile with a 1,048,576-token context window. The dated catalog snapshot records text modalities and interfaces for prompt caching, reasoning controls, structured output, text generation, tool calling.

What context window does DeepSeek V4 Pro 0813 have?

The dated profile lists 1,048,576 tokens of context and up to 384,000 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.

What benchmark evidence is available for DeepSeek V4 Pro 0813?

The 2026-09-06 snapshot includes 3 Artificial Analysis indexes and AutoExacto results for 19 provider observations. Publisher-reported launch results are labeled and are not presented as Kendr measurements; scores from different suites are not treated as interchangeable. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Is DeepSeek V4 Pro 0813 available through Kendr?

This is an independent knowledge profile, not a Kendr-hosted availability claim. Check Kendr's live public model API for currently enabled Kendr aliases.

Does the popularity rank represent DeepSeek V4 Pro 0813's global market share?

DeepSeek V4 Pro 0813 ranked #23 in the cited trailing-7-day third-party catalog usage dataset as of 2026-09-06. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share. No global market-share percentage is inferred when the source does not publish one.

Sources and evidence dates

  1. DeepSeek V4 Pro 0813 third-party catalog record (catalog, checked 2026-09-06)
  2. Third-party model catalog methodology (methodology, checked 2026-09-06)
  3. DeepSeek official model documentation (primary, checked 2026-09-06)
  4. Artificial Analysis capability indices methodology (benchmark, checked 2026-09-06)
  5. DeepSeek V4 Pro 0813 third-party catalog record (benchmark, checked 2026-09-06)