Ling 3.0 Flash Fin vs Sakana Namazu
Ling 3.0 Flash Fin and Sakana Namazu are closely matched at 43.0 and 42.1 on the LLM Stats Score. Ling 3.0 Flash Fin is 19.0x cheaper per token.
InclusionAI · Sakana AI · Updated for 2026
Which is better?
Ling 3.0 Flash Fin and Sakana Namazu are closely matched on the overall LLM Stats Score at 43.0 and 42.1.
On price, Ling 3.0 Flash Fin is roughly 19.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Ling 3.0 Flash Fin also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Ling 3.0 Flash Fin
- cost matters — it's about 19.0x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- you want the most recent training data — it shipped Sep 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.
Individual benchmarks
6 reported for Ling 3.0 Flash Fin · 3 for Sakana Namazu
Ling 3.0 Flash Fin and Sakana Namazudon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Ling 3.0 Flash Fin ($0.06/1M tokens) is 15.8x cheaper than Sakana Namazu ($0.95/1M tokens).
For output processing, Ling 3.0 Flash Fin ($0.18/1M tokens) is 22.2x cheaper than Sakana Namazu ($4.00/1M tokens).
In conclusion, Sakana Namazu is more expensive than Ling 3.0 Flash Fin.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Ling 3.0 Flash Fin accepts 262,144 input tokens compared to Sakana Namazu's 256,000 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while Sakana Namazu is limited to 256,000 tokens.
Input capabilities
Documented input modalities across available providers
Sakana Namazu supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.
Sakana Namazu can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ling 3.0 Flash Fin
Sakana Namazu
Release Timeline
When each model was launched
Ling 3.0 Flash Fin was released on 2026-09-03, while Sakana Namazu was released on 2026-08-03.
Ling 3.0 Flash Fin is 1 month newer than Sakana Namazu.
Sep 3, 2026
2 weeks ago
1mo newerAug 3, 2026
1 months 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
Ling 3.0 Flash Fin is available from DeepInfra. Sakana Namazu is available from Sakana AI.
Ling 3.0 Flash Fin
Sakana Namazu
Outputs Comparison
Judge for yourself.
Run your own prompts against Ling 3.0 Flash Fin and Sakana Namazu side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ling 3.0 Flash Fin vs Sakana Namazu.