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Ling 3.0 Flash Fin vs Parse

Comparing Ling 3.0 Flash Fin and Parse across benchmarks, pricing, and capabilities.

InclusionAI · Cohere · Updated for 2026

Which is better?

Ling 3.0 Flash Fin and Parse trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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 Ling 3.0 Flash Fin

  • you process long inputs — it offers a 262,144 token context window
  • you want the most recent training data — it shipped Sep 2026

Choose Parse

  • you are already invested in the Cohere ecosystem

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.06 / M
— / M
Output price
$0.18 / M
— / M
Context window
262,144
8,192

Individual benchmarks

6 reported for Ling 3.0 Flash Fin · 1 for Parse

No common benchmarks found

Ling 3.0 Flash Fin and Parsedon'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

Model Size

Parameter count comparison

121.7B diff

Ling 3.0 Flash Fin has 121.7B more parameters than Parse, making it 5291.3% larger.

InclusionAI
Ling 3.0 Flash Fin
124.0Bparameters
Cohere
Parse
2.3Bparameters
124.0B
Ling 3.0 Flash Fin
2.3B
Parse

Context Window

Maximum input and output token capacity

Ling 3.0 Flash Fin accepts 262,144 input tokens compared to Parse's 8,192 tokens. Only Ling 3.0 Flash Fin specifies output context (262,144 tokens).

InclusionAI
Ling 3.0 Flash Fin
Input262,144 tokens
Output262,144 tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Tue Sep 08 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Parse supports multimodal inputs, whereas Ling 3.0 Flash Fin does not.

Parse can handle both text and other forms of data like images, making it suitable for multimodal applications.

Ling 3.0 Flash Fin

Text
Images
Audio
Video

Parse

Text
Images
Audio
Video

Release Timeline

When each model was launched

Ling 3.0 Flash Fin was released on 2026-09-03, while Parse was released on 2026-08-27.

Ling 3.0 Flash Fin is 0 month newer than Parse.

Ling 3.0 Flash Fin

Sep 3, 2026

5 days ago

1w newer
Parse

Aug 27, 2026

1 weeks ago

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

Ling 3.0 Flash Fin is available from DeepInfra. Parse is available from Azure, Cohere.

Ling 3.0 Flash Fin

deepinfra logo
Deepinfra
Input Price:Input: $0.06/1MOutput Price:Output: $0.18/1M

Parse

azure logo
Azure
cohere logo
Cohere
* 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 Ling 3.0 Flash Fin and Parse side-by-side, then vote on the output you prefer.

Ling 3.0 Flash Fin
✓ Preferred
Parse
Open in Playground

FAQ

Common questions about Ling 3.0 Flash Fin vs Parse.

Which is better, Ling 3.0 Flash Fin or Parse?

Ling 3.0 Flash Fin (InclusionAI) and Parse (Cohere) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Ling 3.0 Flash Fin compare to Parse in benchmarks?

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%. Parse scores ParseBench: 79.2%.

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

Ling 3.0 Flash Fin supports 262K tokens and Parse supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

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

Key differences include context window (262K vs 8K), multimodal support (no vs yes), licensing (Unknown vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Ling 3.0 Flash Fin and Parse?

Ling 3.0 Flash Fin is developed by InclusionAI and Parse is developed by Cohere.