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Hy4 preview vs Jamba 1.5 Large

Hy4 preview leads the LLM Stats Score 51.5 to 1.2.

Tencent · AI21 Labs · Updated for 2026

Which is better?

Hy4 preview leads the overall LLM Stats Score 51.5 to 1.2, ranking #10 overall.

In the 1 individual benchmarks reported for both models, Hy4 preview wins 1; this is a narrower head-to-head signal than the composite indexes.

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

Choose Hy4 preview

  • overall performance matters — it scores 51.5 and ranks #10 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Aug 2026

Choose Jamba 1.5 Large

  • you want predictable pricing at $2.00/M input and $8.00/M output

At a glance

The differences that matter most.

Hy4 preview
Tencent
Jamba 1.5 Large
AI21 Labs
Core performance indexes
LLM Stats Score
51.5
#10
1.2
#305
Reasoning
51.2
#8
1.2
#296
Cost, coverage & limits
Benchmark wins
1 of 1
0 of 1
Input price
— / M
$2.00 / M
Output price
— / M
$8.00 / M
Context window
—
256,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Hy4 preview
Jamba 1.5 Large
Math
40.3#12
4.9#270
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

32 reported for Hy4 preview · 8 for Jamba 1.5 Large

1 shared

Hy4 preview outperforms in 1 benchmarks (GPQA), while Jamba 1.5 Large is better at 0 benchmarks.

Hy4 preview significantly outperforms across most benchmarks.

Mon Aug 31 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

372.0B diff

Hy4 preview has 372.0B more parameters than Jamba 1.5 Large, making it 93.5% larger.

Tencent
Hy4 preview
770.0Bparameters
AI21 Labs
Jamba 1.5 Large
398.0Bparameters
770.0B
Hy4 preview
398.0B
Jamba 1.5 Large

Context Window

Maximum input and output token capacity

Only Jamba 1.5 Large specifies input context (256,000 tokens). Only Jamba 1.5 Large specifies output context (256,000 tokens).

Tencent
Hy4 preview
Input- tokens
Output- tokens
AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
Mon Aug 31 2026 • llm-stats.com

License

Usage and distribution terms

Hy4 preview is licensed under Apache 2.0, while Jamba 1.5 Large uses Jamba Open Model License.

License differences may affect how you can use these models in commercial or open-source projects.

Hy4 preview

Apache 2.0

Open weights

Jamba 1.5 Large

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

Hy4 preview was released on 2026-08-28, while Jamba 1.5 Large was released on 2024-08-22.

Hy4 preview is 25 months newer than Jamba 1.5 Large.

Hy4 preview

Aug 28, 2026

3 days ago

2.0yr newer
Jamba 1.5 Large

Aug 22, 2024

2.0 years ago

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Hy4 preview's cutoff date is not specified.

We can confirm Jamba 1.5 Large's training data extends to 2024-03-05, but cannot make a direct comparison without Hy4 preview's cutoff date.

Hy4 preview

—

Jamba 1.5 Large

Mar 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Hy4 preview and Jamba 1.5 Large side-by-side, then vote on the output you prefer.

Hy4 preview
✓ Preferred
Jamba 1.5 Large
Open in Playground

FAQ

Common questions about Hy4 preview vs Jamba 1.5 Large.

Which is better, Hy4 preview or Jamba 1.5 Large?

Hy4 preview leads the LLM Stats Score 51.5 to 1.2. Hy4 preview is made by Tencent and Jamba 1.5 Large is made by AI21 Labs. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Hy4 preview compare to Jamba 1.5 Large in benchmarks?

Hy4 preview scores GPQA: 92.3%, Terminal-Bench 2.1: 85.4%, WideSearch: 83.9%, MCP Atlas: 83.7%, SWE-bench Multilingual: 82.9%. Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%.

What are the context window sizes for Hy4 preview and Jamba 1.5 Large?

Hy4 preview supports an unknown number of tokens and Jamba 1.5 Large supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Hy4 preview and Jamba 1.5 Large?

Key differences include LLM Stats Score (51.5 vs 1.2), licensing (Apache 2.0 vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.

Who makes Hy4 preview and Jamba 1.5 Large?

Hy4 preview is developed by Tencent and Jamba 1.5 Large is developed by AI21 Labs.

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