Model decision surface
Compare AI models
Start with DeepSeek V4.1 Flash 1017 and DeepSeek V4 Pro 0813, or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.
Current public data
DeepSeek V4.1 Flash 1017 vs DeepSeek V4 Pro 0813
Live dataset updated 10/21/2026, 11:44:08 PM UTC
Open 1200×630 evidence receipt| Field | DeepSeek V4.1 Flash 1017 DeepSeek | DeepSeek V4 Pro 0813 DeepSeek |
|---|---|---|
| ModelCap position | #70 | #29 |
| Index score | 61.5 | 74.9 |
| Evidence | Measuredpublisher-corpus-prior over 210 held-out anchors (18%); measured predecessor deepseek/deepseek-v4-flash less the succession penalty (69%); 1 specialist-board observation at 2.1% support (13%); shrunk 0.4 toward the measured corpus | Measured3 public benchmark observations across 3 boards |
| Input / 1M | $0.15 | $0.66 |
| Output / 1M | $0.60 | $1.98 |
| Pricing status | fresh | fresh |
| Context | 1M | 1M |
| Providers | 25 | 21 |
| Weight access | Open weights | Open weights |
Decision facts
- DeepSeek V4.1 Flash 1017 is #70; DeepSeek V4 Pro 0813 is #29 on the same current language board.
- Index scores are 61.5 for DeepSeek V4.1 Flash 1017 and 74.9 for DeepSeek V4 Pro 0813. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Both positions use Measured evidence.
- Listed output price per 1M tokens is $0.60 for DeepSeek V4.1 Flash 1017 and $1.98 for DeepSeek V4 Pro 0813. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.60 for DeepSeek V4.1 Flash 1017 versus $2.31 for DeepSeek V4 Pro 0813. DeepSeek V4.1 Flash 1017 costs 74.0% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
- Published context is 1,048,576 tokens for DeepSeek V4.1 Flash 1017 and 1,048,576 for DeepSeek V4 Pro 0813.
- ModelCap currently lists 25 providers for DeepSeek V4.1 Flash 1017 and 21 for DeepSeek V4 Pro 0813.
These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.
Popular comparisons
- Claude Opus 5.5 vs Gemini 4 Argon#2 vs #1 on the ModelCap Index
- Claude Fable 5.1 vs Gemini 4 Argon#3 vs #1 on the ModelCap Index
- Claude Fable 5.1 vs Claude Opus 5.5#3 vs #2 on the ModelCap Index
- Gemini 4 Argon vs Muse Wonder#1 vs #4 on the ModelCap Index
- Claude Opus 5.5 vs Muse Wonder#2 vs #4 on the ModelCap Index
- Claude Fable 5.1 vs Muse Wonder#3 vs #4 on the ModelCap Index
- Gemini 4 Argon vs Muse Spark 1.3#1 vs #5 on the ModelCap Index
- Claude Opus 5.5 vs Muse Spark 1.3#2 vs #5 on the ModelCap Index
- Claude Fable 5.1 vs Muse Spark 1.3#3 vs #5 on the ModelCap Index
- Muse Spark 1.3 vs Muse Wonder#5 vs #4 on the ModelCap Index
- Gemini 3.8 Flash vs Gemini 4 Argon#6 vs #1 on the ModelCap Index
- Claude Opus 5.5 vs Gemini 3.8 Flash#2 vs #6 on the ModelCap Index
- Claude Fable 5.1 vs Gemini 3.8 Flash#3 vs #6 on the ModelCap Index
- Gemini 3.8 Flash vs Muse Wonder#6 vs #4 on the ModelCap Index
- Gemini 3.8 Flash vs Muse Spark 1.3#6 vs #5 on the ModelCap Index
- Gemini 4 Argon vs GPT-6.1 Sol#1 vs #8 on the ModelCap Index
- Claude Opus 5.5 vs GPT-6.1 Sol#2 vs #8 on the ModelCap Index
- Claude Fable 5.1 vs GPT-6.1 Sol#3 vs #8 on the ModelCap Index
- Muse Wonder vs GPT-6.1 Sol#4 vs #8 on the ModelCap Index
- Muse Spark 1.3 vs GPT-6.1 Sol#5 vs #8 on the ModelCap Index
- Gemini 3.8 Flash vs GPT-6.1 Sol#6 vs #8 on the ModelCap Index
- Gemini 4 Argon vs Kimi K3#1 vs #10 on the ModelCap Index
- Claude Opus 5.5 vs Kimi K3#2 vs #10 on the ModelCap Index
- Claude Fable 5.1 vs Kimi K3#3 vs #10 on the ModelCap Index
Each comparison page is a permanent, shareable URL with the same live figures as this tool: ModelCap Index position, API pricing, context window, provider count, weight access and every shared benchmark board.