Ling 3.0 Flash Fin vs MiMo-V2.5
Ling 3.0 Flash Fin leads the LLM Stats Score 43.0 to 35.5. Ling 3.0 Flash Fin is 2.3x cheaper per token.
InclusionAI · Xiaomi · Updated for 2026
Which is better?
Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.0 to 35.5, 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 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.5 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 LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Ling 3.0 Flash Fin
- overall performance matters — it scores 43.0 and ranks #44 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 2.3x cheaper per token
- you want the most recent training data — it shipped Sep 2026
Choose MiMo-V2.5
- you process long inputs — it offers a 1,048,576 token context window
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
6 reported for Ling 3.0 Flash Fin · 14 for MiMo-V2.5
Ling 3.0 Flash Fin outperforms in 1 benchmarks (Finance Agent v2), while MiMo-V2.5 is better at 0 benchmarks.
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, Ling 3.0 Flash Fin ($0.06/1M tokens) is 2.8x cheaper than MiMo-V2.5 ($0.17/1M tokens).
For output processing, Ling 3.0 Flash Fin ($0.18/1M tokens) is 1.9x cheaper than MiMo-V2.5 ($0.34/1M tokens).
In conclusion, MiMo-V2.5 is more expensive than Ling 3.0 Flash Fin.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.5 has 186.8B more parameters than Ling 3.0 Flash Fin, making it 150.6% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.5 accepts 1,048,576 input tokens compared to Ling 3.0 Flash Fin's 262,144 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while MiMo-V2.5 is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
MiMo-V2.5 supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.
MiMo-V2.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Ling 3.0 Flash Fin
MiMo-V2.5
Release Timeline
When each model was launched
Ling 3.0 Flash Fin was released on 2026-09-03, while MiMo-V2.5 was released on 2026-04-22.
Ling 3.0 Flash Fin is 4 months newer than MiMo-V2.5.
Sep 3, 2026
2 weeks ago
4mo newerApr 22, 2026
5 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. MiMo-V2.5 is available from Novita, DeepInfra.
Ling 3.0 Flash Fin
MiMo-V2.5
Outputs Comparison
Judge for yourself.
Run your own prompts against Ling 3.0 Flash Fin and MiMo-V2.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Ling 3.0 Flash Fin vs MiMo-V2.5.