DeepSeek-V4-Flash-Vision-Exp vs Sakana Namazu
Comparing DeepSeek-V4-Flash-Vision-Exp and Sakana Namazu across benchmarks, pricing, and capabilities.
DeepSeek · Sakana AI · Updated for 2026
Which is better?
DeepSeek-V4-Flash-Vision-Exp and Sakana Namazu trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, DeepSeek-V4-Flash-Vision-Exp is roughly 5.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-Vision-Exp also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-Vision-Exp
- cost matters — it's about 5.2x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Sakana Namazu
- you want predictable pricing at $0.95/M input and $4.00/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-Vision-Exp and Sakana Namazudon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-Vision-Exp ($0.22/1M tokens) is 4.3x cheaper than Sakana Namazu ($0.95/1M tokens).
For output processing, DeepSeek-V4-Flash-Vision-Exp ($0.66/1M tokens) is 6.1x cheaper than Sakana Namazu ($4.00/1M tokens).
In conclusion, Sakana Namazu is more expensive than DeepSeek-V4-Flash-Vision-Exp.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-Vision-Exp accepts 1,048,576 input tokens compared to Sakana Namazu's 256,000 tokens. DeepSeek-V4-Flash-Vision-Exp can generate longer responses up to 393,216 tokens, while Sakana Namazu is limited to 256,000 tokens.
Input Capabilities
Supported data types and modalities
Both DeepSeek-V4-Flash-Vision-Exp and Sakana Namazu support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4-Flash-Vision-Exp
Sakana Namazu
Release Timeline
When each model was launched
DeepSeek-V4-Flash-Vision-Exp was released on 2026-08-21, while Sakana Namazu was released on 2026-08-03.
DeepSeek-V4-Flash-Vision-Exp is 1 month newer than Sakana Namazu.
Aug 21, 2026
5 days ago
2w newerAug 3, 2026
3 weeks ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Flash-Vision-Exp is available from DeepSeek. Sakana Namazu is available from Sakana AI.
DeepSeek-V4-Flash-Vision-Exp
Sakana Namazu
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-Vision-Exp and Sakana Namazu side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-Vision-Exp vs Sakana Namazu.