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Gemini Diffusion vs Ling 3.0 Flash Fin

Ling 3.0 Flash Fin leads the LLM Stats Score 43.0 to 0.9.

Google · InclusionAI · Updated for 2026

Which is better?

Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.0 to 0.9, ranking #44 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemini Diffusion

  • you are already invested in the Google ecosystem

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 want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

Gemini Diffusion
Google
Ling 3.0 Flash Fin
InclusionAI
Core performance indexes
LLM Stats Score
0.9
#323
43.0
#44
Reasoning
0.9
#315
44.2
#35
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.06 / M
Output price
— / M
$0.18 / M
Context window
—
262,144

Individual benchmarks

10 reported for Gemini Diffusion · 6 for Ling 3.0 Flash Fin

No common benchmarks found

Gemini Diffusion 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

Context Window

Maximum input and output token capacity

Only Ling 3.0 Flash Fin specifies input context (262,144 tokens). Only Ling 3.0 Flash Fin specifies output context (262,144 tokens).

Google
Gemini Diffusion
Input- tokens
Output- tokens
InclusionAI
Ling 3.0 Flash Fin
Input262,144 tokens
Output262,144 tokens
Tue Sep 15 2026 • llm-stats.com

Release Timeline

When each model was launched

Gemini Diffusion was released on 2025-05-20, while Ling 3.0 Flash Fin was released on 2026-09-03.

Ling 3.0 Flash Fin is 16 months newer than Gemini Diffusion.

Gemini Diffusion

May 20, 2025

1.3 years ago

Ling 3.0 Flash Fin

Sep 3, 2026

1 weeks ago

1.3yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini Diffusion and Ling 3.0 Flash Fin side-by-side, then vote on the output you prefer.

Gemini Diffusion
✓ Preferred
Ling 3.0 Flash Fin
Open in Playground

FAQ

Common questions about Gemini Diffusion vs Ling 3.0 Flash Fin.

Which is better, Gemini Diffusion or Ling 3.0 Flash Fin?

Ling 3.0 Flash Fin leads the LLM Stats Score 43.0 to 0.9. Gemini Diffusion is made by Google and Ling 3.0 Flash Fin is made by InclusionAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemini Diffusion compare to Ling 3.0 Flash Fin in benchmarks?

Gemini Diffusion scores HumanEval: 89.6%, MBPP: 76.0%, Global-MMLU-Lite: 69.1%, LBPP (v2): 56.8%, BigCodeBench: 45.4%. Ling 3.0 Flash Fin scores SpreadSheetBench-v1: 86.5%, Finance Agent v1.1: 69.2%, Finance Agent v2: 59.8%, Tau3 Banking: 41.0%, APEX-Agents: 29.2%.

What are the context window sizes for Gemini Diffusion and Ling 3.0 Flash Fin?

Gemini Diffusion supports an unknown number of tokens and Ling 3.0 Flash Fin supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini Diffusion and Ling 3.0 Flash Fin?

Key differences include LLM Stats Score (0.9 vs 43.0), licensing (Proprietary vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini Diffusion and Ling 3.0 Flash Fin?

Gemini Diffusion is developed by Google and Ling 3.0 Flash Fin is developed by InclusionAI.

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