DeepSeek V4 Flash: Price, Context, Benchmarks, and Release Details
56.2
SI Score (method si-v3-retained-evidence-2)
#78 of 140 ranked
53% confidence 53 percent, Medium confidence — 3 of 7 expected sources in
Coverage 43% of expected source weight · 100% confidence at 80% coverage
Pillar breakdown
Coding (weight 40 percent) 52.4
Math (weight 15 percent) 74.5
Preference (weight 15 percent) 76.1
Reasoning (weight 30 percent) 69.5
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
- Apr 24, 2026models.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - Open weights
- Yesmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗ - License
- not yet reported
- Input modalities
- textmodels.devPublished source fact
Retrieved Oct 9, 2026 · MIT
Open source ↗
Benchmark results
24 results| Benchmark | Raw result | Normalized (0–100) | Pillar |
|---|---|---|---|
| gpqa diamond | 88.1%Official model cards via models.devLab-reported; metric pass@1; transcribed by MIT models.dev catalog; not independently evaluated [variant] preview checkpoint; max effort
Retrieved Oct 9, 2026 · factual citation; MIT transcription Open source ↗ | 88.1 | reasoning |
| hle | 34.8%Official model cards via models.devLab-reported; metric pass@1; transcribed by MIT models.dev catalog; not independently evaluated [variant] preview checkpoint; max effort; without tools
Retrieved Oct 9, 2026 · factual citation; MIT transcription Open source ↗ | 34.8 | reasoning |
| hle tools | 45.1%Official model cards via models.devLab-reported; metric pass@1; transcribed by MIT models.dev catalog; not independently evaluated [variant] preview checkpoint; max effort; with tools
Retrieved Oct 9, 2026 · factual citation; MIT transcription Open source ↗ | 45.1 | reasoning |
| livebench coding code completion 2026_06_25 | 65.2%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 ↗ | 65.2 | coding |
| livebench coding code generation 2026_06_25 | 73.2%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 ↗ | 73.2 | coding |
| livebench coding javascript 2026_06_25 | 54.5%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 ↗ | 54.5 | coding |
| livebench coding python 2026_06_25 | 35%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 ↗ | 35.0 | coding |
| livebench coding typescript 2026_06_25 | 23.3%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 ↗ | 23.3 | coding |
| livebench math amps hard 2026_06_25 | 98%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 ↗ | 98.0 | math |
| livebench math integrals with game 2026_06_25 | 37%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 ↗ | 37.0 | 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 | 86.5%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 ↗ | 86.5 | math |
| livebench math simplify 2026_06_25 | 54.0%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 ↗ | 54.0 | math |
| livebench reasoning connections 2026_06_25 | 89.5%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 ↗ | 89.5 | reasoning |
| livebench reasoning consecutive events 2026_06_25 | 59.9%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 ↗ | 59.9 | reasoning |
| livebench reasoning logic with navigation 2026_06_25 | 64%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 ↗ | 64.0 | 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 | 73.1%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 ↗ | 73.1 | reasoning |
| livebench reasoning zebra puzzle 2026_06_25 | 49.3%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 ↗ | 49.3 | reasoning |
| lmarena text | 1432.1 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 2, 2026
Retrieved Oct 9, 2026 · CC-BY-4.0 Open source ↗ | 76.1 | preference |
| mmlu pro | 86.2%Official model cards via models.devLab-reported; metric EM; transcribed by MIT models.dev catalog; not independently evaluated [variant] preview checkpoint; max effort
Retrieved Oct 9, 2026 · factual citation; MIT transcription Open source ↗ | 86.2 | reasoning |
| swe bench pro | 52.6%Official model cards via models.devLab-reported; metric resolved; transcribed by MIT models.dev catalog; not independently evaluated [variant] preview checkpoint; max effort
Retrieved Oct 9, 2026 · factual citation; MIT transcription Open source ↗ | 52.6 | coding |
| swe bench verified | 79%Official model cards via models.devLab-reported; metric resolved; transcribed by MIT models.dev catalog; not independently evaluated [variant]
Retrieved Oct 9, 2026 · factual citation; MIT transcription Open source ↗ | 79.0 | coding |
| terminal bench v2 0 | 56.9%Official model cards via models.devLab-reported; metric accuracy; transcribed by MIT models.dev catalog; not independently evaluated [variant] preview checkpoint; max effort; 2.0
Retrieved Oct 9, 2026 · factual citation; MIT transcription Open source ↗ | 56.9 | 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 (3)
- Official model cards via models.dev · arrived Oct 8, 2026
- LiveBench · arrived Oct 8, 2026
- LMArena / Arena · arrived Oct 8, 2026
pending Awaiting (4)
- ARC Prize · carries 13% of expected weight
- Epoch AI Benchmarking · carries 25% of expected weight
- Humanity’s Last Exam · carries 13% 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.