DeepSeek-R1 vs Ling 3.0 Flash Fin
Comparing DeepSeek-R1 and Ling 3.0 Flash Fin across benchmarks, pricing, and capabilities.
DeepSeek · InclusionAI · Updated for 2026
Which is better?
DeepSeek-R1 and Ling 3.0 Flash Fin trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Ling 3.0 Flash Fin is roughly 10.7x 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 DeepSeek-R1
- you need open weights you can self-host or fine-tune
Choose Ling 3.0 Flash Fin
- cost matters — it's about 10.7x 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
At a glance
The differences that matter most.
Individual benchmarks
0 reported for DeepSeek-R1 · 6 for Ling 3.0 Flash Fin
DeepSeek-R1 and Ling 3.0 Flash Findon'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, DeepSeek-R1 ($0.55/1M tokens) is 9.2x more expensive than Ling 3.0 Flash Fin ($0.06/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 12.2x more expensive than Ling 3.0 Flash Fin ($0.18/1M tokens).
In conclusion, DeepSeek-R1 is more expensive than Ling 3.0 Flash Fin.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1 has 547.0B more parameters than Ling 3.0 Flash Fin, making it 441.1% larger.
Context Window
Maximum input and output token capacity
Ling 3.0 Flash Fin accepts 262,144 input tokens compared to DeepSeek-R1's 131,072 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while DeepSeek-R1 is limited to 131,072 tokens.
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while Ling 3.0 Flash Fin was released on 2026-09-03.
Ling 3.0 Flash Fin is 20 months newer than DeepSeek-R1.
Jan 20, 2025
1.6 years ago
Sep 3, 2026
5 days ago
1.6yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. Ling 3.0 Flash Fin is available from DeepInfra.
DeepSeek-R1
Ling 3.0 Flash Fin
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1 and Ling 3.0 Flash Fin side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1 vs Ling 3.0 Flash Fin.