DeepSeek V4 Pro 0423
deepseek/deepseek-v4-proDeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window.
Standard pricing
Run this model at its standard rate. Cheap mode currently has no separate discount.
API routing ceilings, including your 5% Free-plan fee. Included usage applies first, then prepaid credits. Cached tokens and tools can have separate charges.
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Playground
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API
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A current API route is listed for this exact model. Gateway configuration is required for live calls.
Provider price + a transparent platform fee
| Rate | Provider baseline | Free plan · 5% fee | Paid plan · 4% fee |
|---|---|---|---|
| Input / 1M tokens | $0.2088 | $0.21924 | $0.217152 |
| Output / 1M tokens | $0.4176 | $0.43848 | $0.434304 |
| API input / 1M tokens | $0.2088 | $0.21924 | $0.217152 |
| API output / 1M tokens | $0.4176 | $0.43848 | $0.434304 |
Legacy chat image rates use the catalog baseline. The dedicated image playground shows separate estimates and settles the provider’s metered usage. API rates are current routing ceilings; final API charges use provider-reported cost plus your fee. Cheapest routing compares eligible OpenRouter and Cheaper Inference rates for the same model; savings are not guaranteed. Cached input or other provider charges may differ. Compare all model rates and verified discounts →
How your plan pays for usage
API and playground share one included allowance. Usage including the fee draws from that allowance first, then your prepaid credits. Plans bill monthly; included usage resets weekly: Free $1, Starter $5, Growth $25, Scale $50.
A $1 provider charge becomes $1.05 on Free or $1.04 on a paid plan before included usage is applied. Plan eligibility still applies in the playground.
Free models and limits
Zero-cost models stay $0, including the fee, and do not consume your dollar allowance. Free accounts can make 1,000 free-model API requests per calendar month, resetting in UTC. Admitted requests count even if the provider fails.
Free includes 20 API requests/minute and 6 playground messages/minute. Paid plans raise these limits. See plan limits.
Before a text API request, Gizmo temporarily reserves included usage and, if necessary, prepaid credit for the model’s full context plus your maximum output. Image jobs reserve twice their displayed estimate. Unused funds return after metering. This hold can exceed the final charge; unconfirmed usage remains marked pending.
Overview
DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding, and long-horizon agent workflows, with strong performance across knowledge, math, and software engineering benchmarks.
Built on the same architecture as DeepSeek V4 Flash, it introduces a hybrid attention system for efficient long-context processing. Reasoning efforts high and xhigh are supported; xhigh maps to max reasoning. It is well suited for complex workloads such as full-codebase analysis, multi-step automation, and large-scale information synthesis, where both capability and efficiency are critical
Benchmarks
Artificial Analysis indices independent, 0–100
Design Arena head-to-head, human-voted
| Category | Elo | Win rate | Rank |
|---|---|---|---|
| 3D scenes | 1284 | 57% | #20 |
| godotgamedev (agent) | 1059 | 34% | #26 |
| Game dev | 1254 | 52.7% | #30 |
| Code | 1257 | 52.1% | #33 |
| ASCII art | 1170 | 46.5% | #35 |
| Websites | 1248 | 50.8% | #37 |
| Web apps (agent) | 1000 | 26.4% | #38 |
| UI components | 1241 | 50.7% | #39 |
Base Model from the model card
| Benchmark (Metric) | # Shots | DeepSeek-V3.2-Base | DeepSeek-V4-Flash-Base | DeepSeek-V4-Pro-Base |
|---|---|---|---|---|
| Architecture | - | MoE | MoE | MoE |
| # Activated Params | - | 37B | 13B | 49B |
| # Total Params | - | 671B | 284B | 1.6T |
| World Knowledge | ||||
| AGIEval (EM) | 0-shot | 80.1 | 82.6 | 83.1 |
| MMLU (EM) | 5-shot | 87.8 | 88.7 | 90.1 |
| MMLU-Redux (EM) | 5-shot | 87.5 | 89.4 | 90.8 |
| MMLU-Pro (EM) | 5-shot | 65.5 | 68.3 | 73.5 |
| MMMLU (EM) | 5-shot | 87.9 | 88.8 | 90.3 |
| C-Eval (EM) | 5-shot | 90.4 | 92.1 | 93.1 |
| CMMLU (EM) | 5-shot | 88.9 | 90.4 | 90.8 |
| MultiLoKo (EM) | 5-shot | 38.7 | 42.2 | 51.1 |
| Simple-QA verified (EM) | 25-shot | 28.3 | 30.1 | 55.2 |
| SuperGPQA (EM) | 5-shot | 45.0 | 46.5 | 53.9 |
| FACTS Parametric (EM) | 25-shot | 27.1 | 33.9 | 62.6 |
| TriviaQA (EM) | 5-shot | 83.3 | 82.8 | 85.6 |
| Language & Reasoning | ||||
| BBH (EM) | 3-shot | 87.6 | 86.9 | 87.5 |
| DROP (F1) | 1-shot | 88.2 | 88.6 | 88.7 |
| HellaSwag (EM) | 0-shot | 86.4 | 85.7 | 88.0 |
| WinoGrande (EM) | 0-shot | 78.9 | 79.5 | 81.5 |
| CLUEWSC (EM) | 5-shot | 83.5 | 82.2 | 85.2 |
| Code & Math | ||||
| BigCodeBench (Pass@1) | 3-shot | 63.9 | 56.8 | 59.2 |
DeepSeek-V4-Pro-Max vs Frontier Models from the model card
| Benchmark (Metric) | Opus-4.6 Max | GPT-5.4 xHigh | Gemini-3.1-Pro High | K2.6 Thinking | GLM-5.1 Thinking | DS-V4-Pro Max |
|---|---|---|---|---|---|---|
| Knowledge & Reasoning | ||||||
| MMLU-Pro (EM) | 89.1 | 87.5 | 91.0 | 87.1 | 86.0 | 87.5 |
| SimpleQA-Verified (Pass@1) | 46.2 | 45.3 | 75.6 | 36.9 | 38.1 | 57.9 |
| Chinese-SimpleQA (Pass@1) | 76.4 | 76.8 | 85.9 | 75.9 | 75.0 | 84.4 |
| GPQA Diamond (Pass@1) | 91.3 | 93.0 | 94.3 | 90.5 | 86.2 | 90.1 |
| HLE (Pass@1) | 40.0 | 39.8 | 44.4 | 36.4 | 34.7 | 37.7 |
| LiveCodeBench (Pass@1) | 88.8 | - | 91.7 | 89.6 | - | 93.5 |
| Codeforces (Rating) | - | 3168 | 3052 | - | - | 3206 |
| HMMT 2026 Feb (Pass@1) | 96.2 | 97.7 | 94.7 | 92.7 | 89.4 | 95.2 |
| IMOAnswerBench (Pass@1) | 75.3 | 91.4 | 81.0 | 86.0 | 83.8 | 89.8 |
| Apex (Pass@1) | 34.5 | 54.1 | 60.9 | 24.0 | 11.5 | 38.3 |
| Apex Shortlist (Pass@1) | 85.9 | 78.1 | 89.1 | 75.5 | 72.4 | 90.2 |
| Long Context | ||||||
| MRCR 1M (MMR) | 92.9 | - | 76.3 | - | - | 83.5 |
| CorpusQA 1M (ACC) | 71.7 | - | 53.8 | - | - | 62.0 |
| Agentic | ||||||
| Terminal Bench 2.0 (Acc) | 65.4 | 75.1 | 68.5 | 66.7 | 63.5 | 67.9 |
| SWE Verified (Resolved) | 80.8 | - | 80.6 | 80.2 | - | 80.6 |
| SWE Pro (Resolved) | 57.3 | 57.7 | 54.2 | 58.6 | 58.4 | 55.4 |
| SWE Multilingual (Resolved) | 77.5 | - | - | 76.7 | 73.3 | 76.2 |
| BrowseComp (Pass@1) | 83.7 | 82.7 | 85.9 | 83.2 | 79.3 | 83.4 |
| HLE w/ tools (Pass@1) | 53.1 | 52.0 | 51.6 | 54.0 | 50.4 | 48.2 |
| GDPval-AA (Elo) | 1619 | 1674 | 1314 | 1482 | 1535 | 1554 |
| MCPAtlas Public (Pass@1) | 73.8 | 67.2 | 69.2 | 66.6 | 71.8 | 73.6 |
Comparison across Modes from the model card
| Benchmark (Metric) | V4-Flash Non-Think | V4-Flash High | V4-Flash Max | V4-Pro Non-Think | V4-Pro High | V4-Pro Max |
|---|---|---|---|---|---|---|
| Knowledge & Reasoning | ||||||
| MMLU-Pro (EM) | 83.0 | 86.4 | 86.2 | 82.9 | 87.1 | 87.5 |
| SimpleQA-Verified (Pass@1) | 23.1 | 28.9 | 34.1 | 45.0 | 46.2 | 57.9 |
| Chinese-SimpleQA (Pass@1) | 71.5 | 73.2 | 78.9 | 75.8 | 77.7 | 84.4 |
| GPQA Diamond (Pass@1) | 71.2 | 87.4 | 88.1 | 72.9 | 89.1 | 90.1 |
| HLE (Pass@1) | 8.1 | 29.4 | 34.8 | 7.7 | 34.5 | 37.7 |
| LiveCodeBench (Pass@1) | 55.2 | 88.4 | 91.6 | 56.8 | 89.8 | 93.5 |
| Codeforces (Rating) | - | 2816 | 3052 | - | 2919 | 3206 |
| HMMT 2026 Feb (Pass@1) | 40.8 | 91.9 | 94.8 | 31.7 | 94.0 | 95.2 |
| IMOAnswerBench (Pass@1) | 41.9 | 85.1 | 88.4 | 35.3 | 88.0 | 89.8 |
| Apex (Pass@1) | 1.0 | 19.1 | 33.0 | 0.4 | 27.4 | 38.3 |
| Apex Shortlist (Pass@1) | 9.3 | 72.1 | 85.7 | 9.2 | 85.5 | 90.2 |
| Long Context | ||||||
| MRCR 1M (MMR) | 37.5 | 76.9 | 78.7 | 44.7 | 83.3 | 83.5 |
| CorpusQA 1M (ACC) | 15.5 | 59.3 | 60.5 | 35.6 | 56.5 | 62.0 |
| Agentic | ||||||
| Terminal Bench 2.0 (Acc) | 49.1 | 56.6 | 56.9 | 59.1 | 63.3 | 67.9 |
| SWE Verified (Resolved) | 73.7 | 78.6 | 79.0 | 73.6 | 79.4 | 80.6 |
| SWE Pro (Resolved) | 49.1 | 52.3 | 52.6 | 52.1 | 54.4 | 55.4 |
| SWE Multilingual (Resolved) | 69.7 | 70.2 | 73.3 | 69.8 | 74.1 | 76.2 |
| BrowseComp (Pass@1) | - | 53.5 | 73.2 | - | 80.4 | 83.4 |
| HLE w/ tools (Pass@1) | - | 40.3 | 45.1 | - | 44.7 | 48.2 |
| MCPAtlas (Pass@1) | 64.0 | 67.4 | 69.0 | 69.4 | 74.2 | 73.6 |
| GDPval-AA (Elo) | - | - | 1395 | - | - | 1554 |
Capabilities
Reasoning is available with effort levels xhigh · high (default high).
Sampling controls: temperature, top_p, top_k, min_p, max_tokens, frequency_penalty, presence_penalty, repetition_penalty. Defaults: top_p 1, temperature 1.
Pricing on Gizmo
These are provider baseline rates before Gizmo’s 5% Free-plan or 4% paid-plan fee. Your included usage covers charges first; overage uses prepaid credits. See the fee-inclusive comparison above.
Provider baseline rates
- Input
- $0.209 / 1M
- Cached input
- $0.072 / 1M
- Output
- $0.418 / 1M
Examples before the platform fee
- Typical chat turn
- $0.00063 2k in · 500 out
- $1 of input
- ≈ 4.79M tokens
- $1 of output
- ≈ 2.39M tokens
- Full context, once
- $0.22
Providers and pricing
One way to run DeepSeek V4 Pro 0423 on Gizmo.
| Provider | Route | Input / 1M | Output / 1M | Context | Uptime 24h |
|---|---|---|---|---|---|
| StreamLake · fp8Lowest price | OpenRouter | $0.21 | $0.42 | 1.02M | 100% |
Rates are each provider’s, per million tokens, before Gizmo’s 5% (Free) or 4% (paid) fee. “Cheapest” routing starts at the top of this list; “Fastest” starts with the model’s maker.
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