Inkling-Small vs Ling 3.0 Flash Fin
Ling 3.0 Flash Fin leads the LLM Stats Score 43.0 to 38.5. Ling 3.0 Flash Fin is 5.8x cheaper per token.
Thinking Machines Lab · InclusionAI · Updated for 2026
Which is better?
Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.0 to 38.5, ranking #44 overall.
In the 1 individual benchmarks reported for both models, Ling 3.0 Flash Fin wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Ling 3.0 Flash Fin is roughly 5.8x 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 Inkling-Small
- you need open weights you can self-host or fine-tune
Choose Ling 3.0 Flash Fin
- overall performance matters — it scores 43.0 and ranks #44 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 5.8x 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.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
24 reported for Inkling-Small · 6 for Ling 3.0 Flash Fin
Inkling-Small outperforms in 0 benchmarks, while Ling 3.0 Flash Fin is better at 1 benchmark (Tau3 Banking).
Ling 3.0 Flash Fin significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Inkling-Small ($0.30/1M tokens) is 5.0x more expensive than Ling 3.0 Flash Fin ($0.06/1M tokens).
For output processing, Inkling-Small ($1.20/1M tokens) is 6.7x more expensive than Ling 3.0 Flash Fin ($0.18/1M tokens).
In conclusion, Inkling-Small is more expensive than Ling 3.0 Flash Fin.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Inkling-Small has 152.0B more parameters than Ling 3.0 Flash Fin, making it 122.6% larger.
Context Window
Maximum input and output token capacity
Ling 3.0 Flash Fin accepts 262,144 input tokens compared to Inkling-Small's 256,000 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while Inkling-Small is limited to 256,000 tokens.
Input capabilities
Documented input modalities across available providers
Inkling-Small supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.
Inkling-Small can handle both text and other forms of data like images, making it suitable for multimodal applications.
Inkling-Small
Ling 3.0 Flash Fin
Release Timeline
When each model was launched
Inkling-Small was released on 2026-07-30, while Ling 3.0 Flash Fin was released on 2026-09-03.
Ling 3.0 Flash Fin is 1 month newer than Inkling-Small.
Jul 30, 2026
1 months ago
Sep 3, 2026
2 weeks ago
1mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Inkling-Small is available from Thinking Machines Lab, DeepInfra. Ling 3.0 Flash Fin is available from DeepInfra.
Inkling-Small
Ling 3.0 Flash Fin
Outputs Comparison
Judge for yourself.
Run your own prompts against Inkling-Small and Ling 3.0 Flash Fin side-by-side, then vote on the output you prefer.
FAQ
Common questions about Inkling-Small vs Ling 3.0 Flash Fin.