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Jamba 1.5 Mini vs Ling 3.1 Flash

Ling 3.1 Flash leads the LLM Stats Score 51.0 to -5.7.

AI21 Labs · InclusionAI · Updated for 2026

Which is better?

Ling 3.1 Flash leads the overall LLM Stats Score 51.0 to -5.7, ranking #15 overall.

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

Choose Jamba 1.5 Mini

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

Choose Ling 3.1 Flash

  • overall performance matters — it scores 51.0 and ranks #15 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.

Jamba 1.5 Mini
AI21 Labs
Ling 3.1 Flash
InclusionAI
Core performance indexes
LLM Stats Score
-5.7
#375
51.0
#15
Reasoning
-5.6
#366
47.5
#26
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.20 / M
— / M
Output price
$0.40 / M
— / M
Context window
256,144
—

Individual benchmarks

8 reported for Jamba 1.5 Mini · 11 for Ling 3.1 Flash

No common benchmarks found

Jamba 1.5 Mini and Ling 3.1 Flashdon'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

508.0B diff

Ling 3.1 Flash has 508.0B more parameters than Jamba 1.5 Mini, making it 976.9% larger.

AI21 Labs
Jamba 1.5 Mini
52.0Bparameters
InclusionAI
Ling 3.1 Flash
560.0Bparameters
52.0B
Jamba 1.5 Mini
560.0B
Ling 3.1 Flash

Context Window

Maximum input and output token capacity

Only Jamba 1.5 Mini specifies input context (256,144 tokens). Only Jamba 1.5 Mini specifies output context (256,144 tokens).

AI21 Labs
Jamba 1.5 Mini
Input256,144 tokens
Output256,144 tokens
InclusionAI
Ling 3.1 Flash
Input- tokens
Output- tokens
Thu Oct 08 2026 • llm-stats.com

Release Timeline

When each model was launched

Jamba 1.5 Mini was released on 2024-08-22, while Ling 3.1 Flash was released on 2026-09-30.

Ling 3.1 Flash is 26 months newer than Jamba 1.5 Mini.

Jamba 1.5 Mini

Aug 22, 2024

2.1 years ago

Ling 3.1 Flash

Sep 30, 2026

1 weeks ago

2.1yr newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Mini has a documented knowledge cutoff of 2024-03-05, while Ling 3.1 Flash's cutoff date is not specified.

We can confirm Jamba 1.5 Mini's training data extends to 2024-03-05, but cannot make a direct comparison without Ling 3.1 Flash's cutoff date.

Jamba 1.5 Mini

Mar 2024

Ling 3.1 Flash

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against Jamba 1.5 Mini and Ling 3.1 Flash side-by-side, then vote on the output you prefer.

Jamba 1.5 Mini
✓ Preferred
Ling 3.1 Flash
Open in Playground

FAQ

Common questions about Jamba 1.5 Mini vs Ling 3.1 Flash.

Which is better, Jamba 1.5 Mini or Ling 3.1 Flash?

Ling 3.1 Flash leads the LLM Stats Score 51.0 to -5.7. Jamba 1.5 Mini is made by AI21 Labs and Ling 3.1 Flash is made by InclusionAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Jamba 1.5 Mini compare to Ling 3.1 Flash in benchmarks?

Jamba 1.5 Mini scores ARC-C: 85.7%, GSM8k: 75.8%, MMLU: 69.7%, TruthfulQA: 54.1%, Arena Hard: 46.1%. Ling 3.1 Flash scores CyberGym: 87.9%, DRACO: 85.5%, FrontierSWE: 75.2%, Multi-Challenge: 69.8%, SkillsBench: 68.7%.

What are the context window sizes for Jamba 1.5 Mini and Ling 3.1 Flash?

Jamba 1.5 Mini supports 256K tokens and Ling 3.1 Flash supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Jamba 1.5 Mini and Ling 3.1 Flash?

Key differences include LLM Stats Score (-5.7 vs 51.0), licensing (Jamba Open Model License vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes Jamba 1.5 Mini and Ling 3.1 Flash?

Jamba 1.5 Mini is developed by AI21 Labs and Ling 3.1 Flash is developed by InclusionAI.

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