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Laguna S 2.1 vs Ling 3.0 Flash Fin

Laguna S 2.1 and Ling 3.0 Flash Fin are closely matched at 40.9 and 43.0 on the LLM Stats Score. Ling 3.0 Flash Fin is 1.4x cheaper per token.

Poolside · InclusionAI · Updated for 2026

Which is better?

Laguna S 2.1 and Ling 3.0 Flash Fin are closely matched on the overall LLM Stats Score at 40.9 and 43.0.

On price, Ling 3.0 Flash Fin is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Laguna S 2.1 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 Laguna S 2.1

  • you process long inputs — it offers a 1,048,576 token context window
  • you need open weights you can self-host or fine-tune

Choose Ling 3.0 Flash Fin

  • cost matters — it's about 1.4x cheaper per token
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

Laguna S 2.1
Poolside
Ling 3.0 Flash Fin
InclusionAI
Core performance indexes
LLM Stats Score
40.9
#53
43.0
#44
Reasoning
40.4
#53
44.2
#35
Agents
24.6
#50
29.2
#37
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.10 / M
$0.06 / M
Output price
$0.20 / M
$0.18 / M
Context window
1,048,576
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Laguna S 2.1
Ling 3.0 Flash Fin
Tool use
17.4#73
20.4#58
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

6 reported for Laguna S 2.1 · 6 for Ling 3.0 Flash Fin

No common benchmarks found

Laguna S 2.1 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, Laguna S 2.1 ($0.10/1M tokens) is 1.7x more expensive than Ling 3.0 Flash Fin ($0.06/1M tokens).

For output processing, Laguna S 2.1 ($0.20/1M tokens) is 1.1x more expensive than Ling 3.0 Flash Fin ($0.18/1M tokens).

In conclusion, Laguna S 2.1 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
Sun Sep 20 2026 • llm-stats.com
Poolside
Laguna S 2.1
Input tokens$0.10
Output tokens$0.20
Best providerPoolside
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

6.0B diff

Ling 3.0 Flash Fin has 6.0B more parameters than Laguna S 2.1, making it 5.1% larger.

Poolside
Laguna S 2.1
118.0Bparameters
InclusionAI
Ling 3.0 Flash Fin
124.0Bparameters
118.0B
Laguna S 2.1
124.0B
Ling 3.0 Flash Fin

Context Window

Maximum input and output token capacity

Laguna S 2.1 accepts 1,048,576 input tokens compared to Ling 3.0 Flash Fin's 262,144 tokens. Only Ling 3.0 Flash Fin specifies output context (262,144 tokens).

Poolside
Laguna S 2.1
Input1,048,576 tokens
Output- tokens
InclusionAI
Ling 3.0 Flash Fin
Input262,144 tokens
Output262,144 tokens
Sun Sep 20 2026 • llm-stats.com

Release Timeline

When each model was launched

Laguna S 2.1 was released on 2026-07-21, while Ling 3.0 Flash Fin was released on 2026-09-03.

Ling 3.0 Flash Fin is 1 month newer than Laguna S 2.1.

Laguna S 2.1

Jul 21, 2026

2 months ago

Ling 3.0 Flash Fin

Sep 3, 2026

2 weeks ago

1mo 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

Laguna S 2.1 is available from Poolside. Ling 3.0 Flash Fin is available from DeepInfra.

Laguna S 2.1

poolside logo
Poolside
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M

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 Laguna S 2.1 and Ling 3.0 Flash Fin side-by-side, then vote on the output you prefer.

Laguna S 2.1
✓ Preferred
Ling 3.0 Flash Fin
Open in Playground

FAQ

Common questions about Laguna S 2.1 vs Ling 3.0 Flash Fin.

Which is better, Laguna S 2.1 or Ling 3.0 Flash Fin?

Laguna S 2.1 and Ling 3.0 Flash Fin are closely matched on the LLM Stats Score at 40.9 and 43.0. Laguna S 2.1 is made by Poolside 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 Laguna S 2.1 compare to Ling 3.0 Flash Fin in benchmarks?

Laguna S 2.1 scores SWE-bench Multilingual: 78.5%, Terminal-Bench 2.1: 70.2%, SWE-Bench Pro: 59.4%, Toolathlon: 49.7%, SWE Atlas - Codebase QnA: 46.2%. 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 Laguna S 2.1 cheaper than Ling 3.0 Flash Fin?

Ling 3.0 Flash Fin is 1.7x cheaper for input tokens. Laguna S 2.1 costs $0.10/M input and $0.20/M output via poolside. Ling 3.0 Flash Fin costs $0.06/M input and $0.18/M output via deepinfra.

What are the context window sizes for Laguna S 2.1 and Ling 3.0 Flash Fin?

Laguna S 2.1 supports 1.0M 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 Laguna S 2.1 and Ling 3.0 Flash Fin?

Key differences include LLM Stats Score (40.9 vs 43.0), context window (1.0M vs 262K), input pricing ($0.10 vs $0.06/M), licensing (OpenMDW License v1.1 vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes Laguna S 2.1 and Ling 3.0 Flash Fin?

Laguna S 2.1 is developed by Poolside and Ling 3.0 Flash Fin is developed by InclusionAI.

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