DeepSeek V4 Flash Vision Exp: Price, Context, Benchmarks, and Release Details
54.8
SI Score (method si-v3-retained-evidence-2)
21% confidence 21 percent, Low confidence — 2 of 7 expected sources in
Coverage 17% of expected source weight · 100% confidence at 80% coverage
Pillar breakdown
Coding (weight 40 percent) 67.5
Math (weight 15 percent) 83.3
Preference (weight 15 percent) —
Reasoning (weight 30 percent) 88.5
Pillar weights: reasoning 30% · math 15% · coding 40% · preference 15%. Benchmark results use fixed 0–100 scales before averaging; incomplete evidence is shrunk toward 50.
Facts
- Input price / 1M
- $0.30LiteLLMFirst-party API Standard token rate; MIT LiteLLM transcription. Provider documentation: https://api-docs.deepseek.com/quick_start/pricing. Exact endpoint only; cache/batch/long-context rates excluded
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Output price / 1M
- $1.20LiteLLMFirst-party API Standard token rate; MIT LiteLLM transcription. Provider documentation: https://api-docs.deepseek.com/quick_start/pricing. Exact endpoint only; cache/batch/long-context rates excluded
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Context window
- 1Mmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Max output
- 384Kmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Released
- Aug 21, 2026models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Open weights
- YesHugging Face HubPublic Hub repo with weight files; gating/repo upload date is not release date
Retrieved Oct 9, 2026 · factual metadata; model-specific licenses
Open source ↗ - License
- mitHugging Face HubPublished source fact
Retrieved Oct 9, 2026 · factual metadata; model-specific licenses
Open source ↗ - Input modalities
- text, imagemodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
Benchmark results
17 results| Benchmark | Raw result | Normalized (0–100) | Pillar |
|---|---|---|---|
| livebench coding code completion 2026_06_25 | 67.4%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 67.4 | coding |
| livebench coding code generation 2026_06_25 | 69.0%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 69.0 | coding |
| livebench coding javascript 2026_06_25 | 63.6%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 63.6 | coding |
| livebench coding python 2026_06_25 | 75%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 75.0 | coding |
| livebench coding typescript 2026_06_25 | 56.7%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 56.7 | coding |
| livebench math amps hard 2026_06_25 | 88%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 88.0 | math |
| livebench math integrals with game 2026_06_25 | 76%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 76.0 | math |
| livebench math math comp 2026_06_25 | 97.1%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 97.1 | math |
| livebench math olympiad 2026_06_25 | 90.2%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 90.2 | math |
| livebench math simplify 2026_06_25 | 65.1%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 65.1 | math |
| livebench reasoning connections 2026_06_25 | 99.3%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 99.3 | reasoning |
| livebench reasoning consecutive events 2026_06_25 | 90.0%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 90.0 | reasoning |
| livebench reasoning logic with navigation 2026_06_25 | 68%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 68.0 | reasoning |
| livebench reasoning spatial 2026_06_25 | 96%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 96.0 | reasoning |
| livebench reasoning theory of mind 2026_06_25 | 78.8%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 78.8 | reasoning |
| livebench reasoning zebra puzzle 2026_06_25 | 98.8%LiveBenchLiveBench subtask result; dataset edition 2026_06_25; publication time is HTTP Last-Modified of the score CSV, not the dataset edition or individual evaluation date [variant] 2026_06_25Published Oct 7, 2026
Retrieved Oct 9, 2026 · factual citation; Apache-2.0 code Open source ↗ | 98.8 | reasoning |
| terminal bench v2 1 | 83.9%Official model cards via models.devLab-reported; metric score; transcribed by MIT models.dev catalog; not independently evaluated [variant] max effort; DeepSeek Harness minimal mode; 2.1
Retrieved Oct 9, 2026 · factual citation; MIT transcription Open source ↗ | 83.9 | coding |
Normalization uses fixed absolute 0–100 scales for each unit, independently of other models that have a result on each benchmark. Coverage and evidence breadth still affect the composite; compare the evaluation conditions before reading a small score gap as decisive. “lab-reported” marks the provider's own published figure.
Sources: in and pending
in Reported (2)
- Official model cards via models.dev · arrived Oct 8, 2026
- LiveBench · arrived Oct 8, 2026
pending Awaiting (5)
- ARC Prize · carries 13% of expected weight
- Epoch AI Benchmarking · carries 25% of expected weight
- Humanity’s Last Exam · carries 13% of expected weight
- LMArena / Arena · carries 25% of expected weight
- Terminal-Bench · carries 6% of expected weight
The confidence % rises as pending sources publish. Some sources never cover some models — that is why 100% confidence arrives at 80% of expected weight, not at full coverage.