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GLM-4.7-Flash vs Ling 3.0 Flash Fin

Ling 3.0 Flash Fin leads the LLM Stats Score 43.2 to 23.5. Ling 3.0 Flash Fin is 1.7x cheaper per token.

Zhipu AI · InclusionAI · Updated for 2026

Which is better?

Ling 3.0 Flash Fin leads the overall LLM Stats Score 43.2 to 23.5, ranking #41 overall.

On price, Ling 3.0 Flash Fin is roughly 1.7x 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 GLM-4.7-Flash

  • you need open weights you can self-host or fine-tune

Choose Ling 3.0 Flash Fin

  • overall performance matters — it scores 43.2 and ranks #41 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • cost matters — it's about 1.7x 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.

GLM-4.7-Flash
Zhipu AI
Ling 3.0 Flash Fin
InclusionAI
Core performance indexes
LLM Stats Score
23.5
#174
43.2
#41
Reasoning
23.5
#163
44.6
#33
Agents
4.6
#153
29.5
#36
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.07 / M
$0.06 / M
Output price
$0.40 / M
$0.18 / M
Context window
128,000
262,144

Individual benchmarks

6 reported for GLM-4.7-Flash · 6 for Ling 3.0 Flash Fin

No common benchmarks found

GLM-4.7-Flash 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

Ling 3.0 Flash Fin costs less

For input processing, GLM-4.7-Flash ($0.07/1M tokens) is 1.2x more expensive than Ling 3.0 Flash Fin ($0.06/1M tokens).

For output processing, GLM-4.7-Flash ($0.40/1M tokens) is 2.2x more expensive than Ling 3.0 Flash Fin ($0.18/1M tokens).

In conclusion, GLM-4.7-Flash is more expensive than Ling 3.0 Flash Fin.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Sep 15 2026 • llm-stats.com
Zhipu AI
GLM-4.7-Flash
Input tokens$0.07
Output tokens$0.40
Best providerUnknown Organization
InclusionAI
Ling 3.0 Flash Fin
Input tokens$0.06
Output tokens$0.18
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

94.0B diff

Ling 3.0 Flash Fin has 94.0B more parameters than GLM-4.7-Flash, making it 313.3% larger.

Zhipu AI
GLM-4.7-Flash
30.0Bparameters
InclusionAI
Ling 3.0 Flash Fin
124.0Bparameters
30.0B
GLM-4.7-Flash
124.0B
Ling 3.0 Flash Fin

Context Window

Maximum input and output token capacity

Ling 3.0 Flash Fin accepts 262,144 input tokens compared to GLM-4.7-Flash's 128,000 tokens. Ling 3.0 Flash Fin can generate longer responses up to 262,144 tokens, while GLM-4.7-Flash is limited to 16,384 tokens.

Zhipu AI
GLM-4.7-Flash
Input128,000 tokens
Output16,384 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

GLM-4.7-Flash was released on 2026-01-19, while Ling 3.0 Flash Fin was released on 2026-09-03.

Ling 3.0 Flash Fin is 8 months newer than GLM-4.7-Flash.

GLM-4.7-Flash

Jan 19, 2026

7 months ago

Ling 3.0 Flash Fin

Sep 3, 2026

1 weeks ago

7mo 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

Provider Availability

GLM-4.7-Flash is available from ZAI. Ling 3.0 Flash Fin is available from DeepInfra.

GLM-4.7-Flash

z logo
Unknown Organization
Input Price:Input: $0.07/1MOutput Price:Output: $0.40/1M

Ling 3.0 Flash Fin

deepinfra logo
Deepinfra
Input Price:Input: $0.06/1MOutput Price:Output: $0.18/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-4.7-Flash and Ling 3.0 Flash Fin side-by-side, then vote on the output you prefer.

GLM-4.7-Flash
✓ Preferred
Ling 3.0 Flash Fin
Open in Playground

FAQ

Common questions about GLM-4.7-Flash vs Ling 3.0 Flash Fin.

Which is better, GLM-4.7-Flash or Ling 3.0 Flash Fin?

Ling 3.0 Flash Fin leads the LLM Stats Score 43.2 to 23.5. GLM-4.7-Flash is made by Zhipu AI 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 GLM-4.7-Flash compare to Ling 3.0 Flash Fin in benchmarks?

GLM-4.7-Flash scores AIME 2025: 91.6%, Tau-bench: 79.5%, GPQA: 75.2%, SWE-Bench Verified: 59.2%, BrowseComp: 42.8%. 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%.

Is GLM-4.7-Flash cheaper than Ling 3.0 Flash Fin?

Ling 3.0 Flash Fin is 1.2x cheaper for input tokens. GLM-4.7-Flash costs $0.07/M input and $0.40/M output via z. Ling 3.0 Flash Fin costs $0.06/M input and $0.18/M output via deepinfra.

What are the context window sizes for GLM-4.7-Flash and Ling 3.0 Flash Fin?

GLM-4.7-Flash supports 128K 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 GLM-4.7-Flash and Ling 3.0 Flash Fin?

Key differences include LLM Stats Score (23.5 vs 43.2), context window (128K vs 262K), input pricing ($0.07 vs $0.06/M), licensing (MIT vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-4.7-Flash and Ling 3.0 Flash Fin?

GLM-4.7-Flash is developed by Zhipu AI and Ling 3.0 Flash Fin is developed by InclusionAI.

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