DeepSeek V4 Pro 0813
DeepSeek · Proprietary · rank 31 · bench-align-v5
Canonical iddeepseek-v4-pro-max
Access typeProprietary
Blended $/1M$0.5475% input / 25% output
Capability shape
Seven axes from the ranking source. A missing axis is drawn as a gap.
Runtime service evidence
Measured values with the date they were observed. Nothing is inferred from a sibling model or a provider claim.
Time to first token: latency to the first answer chunk (Artificial Analysis, via BenchLM). Reasoning models include thinking time, so values can run to tens or hundreds of seconds.
Evidence key: Observed
| Measurement | Value | Observed | Last good | Evidence |
|---|---|---|---|---|
| Time to first token | 23.62 s | 2026-09-17 | 2026-09-17 | |
| Throughput | 91 tok/s | 2026-09-17 | 2026-09-17 |
Regional or per-endpoint measurements appear only when the API supplies them; none are modelled here.
Endpoint and price matrix
Every published price component, including cache reads and writes.
| Component | USD | Evidence |
|---|---|---|
| Input / 1M tokens | $0.44 | |
| Output / 1M tokens | $0.87 | |
| Cache read / 1M tokens | $0.0036 | |
| Cache write / 1M tokens | Unavailable | |
| Blended / 1M (75% input / 25% output) | $0.54 |
Self-hosted listingDeepSeek's pricing page checked August 12, 2026 identifies the current `deepseek-v4-pro` API version as DeepSeek-V4-Pro-0813 and lists $0.435 cache-miss input / $0.003625 cache-hit input / $0.87 output per million tokens. DeepSeek warns that an overall API price increase is planned but has not published the new rates or effective date. DeepSeek has not published weights for the 0813 hosted checkpoint. DeepSeek's September 10, 2026 V4.1 Flash announcement said `deepseek-v4-pro` requests would route to DeepSeek-V4.1-Flash and bill at the V4.1 Flash rate from 04:00 UTC on September 14, 2026 until V4.1 Pro launches. DeepSeek's pricing page, read September 17, 2026, says V4 Pro API service continues after September 14, 2026 with the billing method unchanged, and that DeepSeek will give notice of any change; the September 10 post had not been edited when read the same day (https://api-docs.deepseek.com/news/news260910, https://api-docs.deepseek.com/quick_start/pricing). The same page lists `deepseek-v4-pro` at peak $1.32 cache-miss input / $0.044 cache-hit input / $3.96 output per million tokens, with off-peak at half; the stored values in this row are the August 12 check and have not been refreshed to those rates.The rates above are a hosted price matched from another provider, not a first-party list price.
Workload-aware monthly cost example
10 conversations per day × 8 messages × 22 active days, 1200 input and 400 output tokens per message, no cache. This uses the same calculator as the cost simulator, so an unavailable applicable rate makes the example unavailable too.
Benchmark record
62 matched benchmark rows with their published value, unit, and provenance.
Knowledge
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| GPQA Graduate-Level Google-Proof Q&A | 90.1 | 448 questions | Graduate level | GPQA: A Graduate-Level Google-Proof Q&A Benchmark |
| GPQA-D GPQA Diamond | 90.1 | Graduate-level science questions | Graduate level | Trinity-Large-Thinking: Scaling an Open Source Frontier Agent |
| MMLU-Pro Massive Multitask Language Understanding Professional | 87.5 | Multiple subjects | Professional level | MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark |
| HLE Humanity's Last Exam | 42.7 | Expert-level questions | Frontier expert level | Humanity's Last Exam |
| Artificial Analysis Intelligence Index Artificial Analysis Intelligence Index | 53.2 | Cross-benchmark intelligence index | Display-only external reference | Artificial Analysis |
| AA-GPQA Diamond Artificial Analysis GPQA Diamond | 92.8 | Graduate-level science questions | Graduate-level science reasoning | Artificial Analysis GPQA Diamond Benchmark Leaderboard |
| AA-HLE Artificial Analysis Humanity's Last Exam | 41.0 | Expert-level questions | Frontier expert reasoning | Artificial Analysis Humanity's Last Exam Benchmark Leaderboard |
| AA-Omniscience Index Artificial Analysis Omniscience Index | 0.8 | Knowledge questions | Broad factual knowledge | AA-Omniscience: Knowledge and Hallucination Benchmark |
| AA-Omniscience Accuracy Artificial Analysis Omniscience Accuracy | 49.1 | Knowledge questions | Broad knowledge | Artificial Analysis model benchmarks |
| AA-Omniscience Hallucination Rate Artificial Analysis Omniscience Hallucination Rate | 94.1 | Knowledge questions | Factuality | Artificial Analysis model benchmarks |
| SimpleQA Measuring Short-Form Factuality in Large Language Models | 57.9 | Factual questions | Factual accuracy focused | Measuring short-form factuality in large language models |
| Chinese-SimpleQA Chinese-SimpleQA | 84.4 | Chinese factual questions | Factual accuracy focused | DeepSeek-V4 Technical Report |
| GPQA Diamond (Vals) GPQA Diamond, Vals AI run | 92.4 | Graduate-level science questions | Expert reasoning | Vals AI GPQA Diamond, Vals AI run leaderboard |
| MMLU-Pro (Vals) MMLU-Pro, Vals AI run | 87.0 | Academic multiple-choice questions | Broad academic knowledge | Vals AI MMLU-Pro, Vals AI run leaderboard |
Coding
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| Terminal-Bench 2.1 Terminal-Bench 2.1 (provider run) | 87.9 | Terminal-based software-agent tasks | Professional software engineering | DeepSeek V4 Flash 0731 update |
| Codeforces Codeforces Rating | 3206.0 | Competitive programming contests | Elite competitive programming | DeepSeek-V4 Technical Report |
| Terminal-Bench 2.0 Terminal-Bench 2.0 | 67.9 | Terminal-based software tasks | Professional software engineering | Terminal-Bench 2.0 |
| SWE-bench Verified Software Engineering Benchmark Verified | 80.6 | 500 verified issues | Professional software engineering | SWE-bench: Can Language Models Resolve Real-World GitHub Issues? |
| LiveCodeBench Pass@1-COT LiveCodeBench Pass@1 with Chain-of-Thought | 93.5 | DeepSeek-V4 report evaluation window | Competitive programming level | DeepSeek-V4 technical report |
| SWE-bench Pro SWE-bench Pro | 55.4 | 1,865 repository problems | Long-horizon professional engineering | SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks? |
| OpenHarmony Bench OpenHarmony Bench v1.0 | 59.0 | 153 app-development and bug-fix tasks | End-to-end OpenHarmony application development | OpenHarmony Bench: Evaluating LLMs and Coding Agents on OpenHarmony App Development |
| SWE Multilingual SWE Multilingual | 76.2 | Multilingual software-engineering tasks | Professional software engineering | MiniMax M2.7: Early Echoes of Self-Evolution |
| Vibe Code Bench Vibe Code Bench v1.1 | 49.93 | End-to-end web application builds | End-to-end software delivery | Vibe Code Bench: Evaluating AI Models on End-to-End Web Application Development |
| NL2Repo NL2Repo | 61.5 | Natural language to repository tasks | System-level software comprehension | MiniMax M2.7: Early Echoes of Self-Evolution |
| DSBench-FullStack DeepSeek DSBench FullStack | 71.1 | Internal full-stack coding-agent tasks | Full-stack software engineering | DeepSeek V4 Flash 0731 update |
| DSBench-Hard DeepSeek DSBench Hard | 67.2 | Internal hard coding-agent tasks | Advanced coding-agent challenges | DeepSeek V4 Flash 0731 update |
| AA Coding Index Artificial Analysis Coding Index | 68.8 | Cross-benchmark coding index | Display-only external reference | Artificial Analysis model leaderboards |
| AA-SciCode Artificial Analysis SciCode | 51.0 | Scientific coding subproblems | Scientific programming | Artificial Analysis SciCode Benchmark Leaderboard |
| LiveCodeBench (Vals) LiveCodeBench, Vals AI run | 87.5 | Competitive programming problems (easy, medium, hard) | Frontier coding | Vals AI LiveCodeBench, Vals AI run leaderboard |
| SWE-bench (Vals) SWE-bench, Vals AI run | 96.4 | Real repository issues by human time bucket | Frontier coding agents | Vals AI SWE-bench, Vals AI run leaderboard |
| DeepSWE DeepSWE | 62.7 | 113 software engineering tasks across 91 repositories and 5 languages | Long-horizon software engineering | DeepSWE benchmark blog |
Mathematics
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| HMMT Feb 2026 Harvard-MIT Mathematics Tournament February 2026 | 95.2 | Competition math problems | Olympiad-style mathematics | Qwen3.6 launch benchmarks |
| IMOAnswerBench IMOAnswerBench | 89.8 | Advanced mathematical answer generation | Olympiad-level mathematics | DeepSeek-V4 Technical Report |
| Apex Apex | 38.3 | Advanced mathematical reasoning | Frontier math reasoning | DeepSeek-V4 Technical Report |
| Apex Shortlist Apex Shortlist | 90.2 | Advanced mathematical reasoning | Frontier math reasoning | DeepSeek-V4 Technical Report |
Reasoning
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| MRCR 1M MRCR 1M | 83.5 | Million-token retrieval | Million-token long context | DeepSeek-V4 Technical Report |
| CorpusQA 1M CorpusQA 1M | 62.0 | Million-token corpus question answering | Million-token long context | DeepSeek-V4 Technical Report |
| AA-LCR Artificial Analysis Long Context Reasoning | 80.3 | Long-context reasoning tasks | Long-context reasoning | Artificial Analysis model benchmarks |
| MLCR-AA Medical Long Context Reasoning (MLCR-AA) | 17.8 | Long, fragmented medical-record reasoning | Long-context medical reasoning | Medical Long Context Reasoning (MLCR-AA) |
| CritPt Critical Physics Tasks | 18.0 | Research-level physics questions | Research-level physics reasoning | CritPt Benchmark Leaderboard |
Instruction Following
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AA-IFBench Artificial Analysis IFBench | 76.5 | Verifiable instruction constraints | Instruction precision | Artificial Analysis IFBench Benchmark Leaderboard |
Agentic
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| AA AutomationBench Artificial Analysis AutomationBench | 56.7 | Business-process automation tasks | Agentic automation | Artificial Analysis AutomationBench Benchmark Leaderboard |
| AA EnterpriseOps-Gym Artificial Analysis EnterpriseOps-Gym | 49.6 | Enterprise operations workflows | Enterprise agent operations | Artificial Analysis EnterpriseOps-Gym Benchmark Leaderboard |
| AA Tau3 Banking Artificial Analysis Tau3-Banking | 39.6 | Banking tool-use workflows | Agentic banking workflows | Artificial Analysis Tau3-Banking Benchmark Leaderboard |
| Terminal-Bench 2.0 Terminal-Bench 2.0 | 67.9 | Terminal-based software tasks | Professional software engineering | Terminal-Bench 2.0 |
| Terminal-Bench 2.1 Terminal-Bench 2.1 (provider run) | 87.9 | Terminal-based software-agent tasks | Professional software engineering | DeepSeek V4 Flash 0731 update |
| BrowseComp BrowseComp | 83.4 | Research questions requiring browsing | Hard web research | BrowseComp |
| HLE w/ tools Humanity's Last Exam with tools | 60.0 | Expert questions with tool use | Frontier tool-augmented reasoning | DeepSeek-V4 Technical Report |
| GDPval-AA GDPval-AA | 1306 | Agentic real-world work tasks | Professional agentic workflows | DeepSeek-V4 Technical Report |
| GDPval-AA GDPval-AA normalized | 54.5 | Economically valuable tasks | Professional agentic workflows | Artificial Analysis model benchmarks |
| AA Agentic Index Artificial Analysis Agentic Index | 49.6 | Cross-benchmark agentic index | Display-only external reference | Artificial Analysis model leaderboards |
| AA Terminal-Bench 4.0 Artificial Analysis Terminal-Bench v4.0 | 14.1 | Terminal-based agent tasks | Agentic software engineering | Artificial Analysis Terminal-Bench v4.0 Benchmark Leaderboard |
| APEX-Agents-AA APEX-Agents-AA | 24.3 | 452 professional-services agent tasks | Long-horizon workplace agent tasks | APEX-Agents-AA Benchmark Leaderboard |
| CyberGym CyberGym | 83.3 | 1,507 vulnerability analysis instances | Real-world cybersecurity | CyberGym: Evaluating AI Agents' Real-World Cybersecurity Capabilities at Scale |
| MCP Atlas MCP Atlas | 73.6 | Tool-integrated agent tasks | Advanced tool use | Introducing GPT-5.4 mini and nano |
| Toolathlon Toolathlon | 51.8 | Multi-tool workflows | Advanced tool use | Introducing GPT-5.4 mini and nano |
| Toolathlon-Verified Toolathlon-Verified | 74.1 | Verified multi-tool workflows | Advanced tool use | Kimi K3: Open Frontier Intelligence |
| AutomationBench AutomationBench | 31.8 | 600 public automation tasks | Long-horizon automation | Kimi K3: Open Frontier Intelligence |
| Agents' Last Exam Agents' Last Exam | 25.7 | Agent tasks | Advanced agentic work | DeepSeek V4 Flash 0731 update |
| τ²-bench results τ²-Bench Tool-Agent-User Evaluation | 96.2 | Airline, retail, and telecom customer-service task sets | Dual-control customer-service workflows | τ²-Bench: Evaluating Conversational Agents in a Dual-Control Environment |
| Terminal-Bench 2.1 (Vals) Terminal-Bench 2.1, Vals AI run | 54.7 | Difficult terminal tasks | Frontier agentic | Vals AI Terminal-Bench 2.1, Vals AI run leaderboard |
Multimodal & Grounded
| Benchmark | Value | Tasks | Difficulty | Provenance |
|---|---|---|---|---|
| Design Arena Website Design Arena Website Elo | 1258 | Website generation comparisons | Design and website generation | OpenRouter Grok 4.3 benchmarks |
Lifecycle and limitations log
Lifecycle events the source associates with this model, plus what this profile does not claim.
No lifecycle event references this model.
That is not evidence the model has no lifecycle plan — only that this source published none.
What this profile does not claimValues are reproduced exactly as their sources published them, in the units those sources declared; none are converted, interpolated, or averaged across providers. Any field marked unavailable was attempted and not returned — the attempt timestamp is in each badge. Last attempted fetch for this model’s score: 2026-09-17 17:17 UTC.