Model Comparison

DeepSeek-V3.2-Speciale vs Jamba 1.5 MiniWhich is better in 2026?

Comparing DeepSeek-V3.2-Speciale and Jamba 1.5 Mini across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V3.2-Speciale vs Jamba 1.5 Mini — which is better?

DeepSeek-V3.2-Speciale (by DeepSeek) and Jamba 1.5 Mini (by AI21 Labs) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

On price, Jamba 1.5 Mini is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Jamba 1.5 Mini also accepts a larger context window (256,144 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek-V3.2-Speciale if…

  • you want the most recent training data — it shipped Dec 2025

Choose Jamba 1.5 Mini if…

  • cost matters — it's about 1.3x cheaper per token
  • you process long inputs — it offers a 256,144 token context window
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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2-Speciale and Jamba 1.5 Minidon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Jamba 1.5 Mini costs less

For input processing, DeepSeek-V3.2-Speciale ($0.28/1M tokens) is 1.4x more expensive than Jamba 1.5 Mini ($0.20/1M tokens).

For output processing, DeepSeek-V3.2-Speciale ($0.42/1M tokens) is 1.0x more expensive than Jamba 1.5 Mini ($0.40/1M tokens).

In conclusion, DeepSeek-V3.2-Speciale is more expensive than Jamba 1.5 Mini.*

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

Lowest available price from all providers
Mon Jun 15 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Speciale
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
AI21 Labs
Jamba 1.5 Mini
Input tokens$0.20
Output tokens$0.40
Best providerAWS Bedrock
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

633.0B diff

DeepSeek-V3.2-Speciale has 633.0B more parameters than Jamba 1.5 Mini, making it 1217.3% larger.

DeepSeek
DeepSeek-V3.2-Speciale
685.0Bparameters
AI21 Labs
Jamba 1.5 Mini
52.0Bparameters
685.0B
DeepSeek-V3.2-Speciale
52.0B
Jamba 1.5 Mini

Context Window

Maximum input and output token capacity

Jamba 1.5 Mini accepts 256,144 input tokens compared to DeepSeek-V3.2-Speciale's 131,072 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while DeepSeek-V3.2-Speciale is limited to 131,072 tokens.

DeepSeek
DeepSeek-V3.2-Speciale
Input131,072 tokens
Output131,072 tokens
AI21 Labs
Jamba 1.5 Mini
Input256,144 tokens
Output256,144 tokens
Mon Jun 15 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek-V3.2-Speciale is licensed under MIT, while Jamba 1.5 Mini uses Jamba Open Model License.

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

DeepSeek-V3.2-Speciale

MIT

Open weights

Jamba 1.5 Mini

Jamba Open Model License

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Speciale was released on 2025-12-01, while Jamba 1.5 Mini was released on 2024-08-22.

DeepSeek-V3.2-Speciale is 16 months newer than Jamba 1.5 Mini.

DeepSeek-V3.2-Speciale

Dec 1, 2025

6 months ago

1.3yr newer
Jamba 1.5 Mini

Aug 22, 2024

1.8 years ago

Knowledge Cutoff

When training data ends

Jamba 1.5 Mini has a documented knowledge cutoff of 2024-03-05, while DeepSeek-V3.2-Speciale'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 DeepSeek-V3.2-Speciale's cutoff date.

DeepSeek-V3.2-Speciale

—

Jamba 1.5 Mini

Mar 2024

Provider Availability

DeepSeek-V3.2-Speciale is available from DeepSeek. Jamba 1.5 Mini is available from Bedrock, Google.

DeepSeek-V3.2-Speciale

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

Jamba 1.5 Mini

bedrock logo
AWS Bedrock
Input Price:Input: $0.20/1MOutput Price:Output: $0.40/1M
google logo
Google
Input Price:Input: $0.20/1MOutput Price:Output: $0.40/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek

No standout differentiators in the data we have for this pair.

AI21 Labs
Larger context window (256,144 tokens)
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Speciale
AI21 Labs
Jamba 1.5 Mini

FAQ

Common questions about DeepSeek-V3.2-Speciale vs Jamba 1.5 Mini.

Which is better, DeepSeek-V3.2-Speciale or Jamba 1.5 Mini?

DeepSeek-V3.2-Speciale (DeepSeek) and Jamba 1.5 Mini (AI21 Labs) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek-V3.2-Speciale compare to Jamba 1.5 Mini in benchmarks?

DeepSeek-V3.2-Speciale scores HMMT 2025: 99.2%, AIME 2025: 96.0%, CodeForces: 90.0%, t2-bench: 80.3%, SWE-Bench Verified: 73.1%. Jamba 1.5 Mini scores ARC-C: 85.7%, GSM8k: 75.8%, MMLU: 69.7%, TruthfulQA: 54.1%, Arena Hard: 46.1%.

Is DeepSeek-V3.2-Speciale cheaper than Jamba 1.5 Mini?

Jamba 1.5 Mini is 1.4x cheaper for input tokens. DeepSeek-V3.2-Speciale costs $0.28/M input and $0.42/M output via deepseek. Jamba 1.5 Mini costs $0.20/M input and $0.40/M output via bedrock.

What are the context window sizes for DeepSeek-V3.2-Speciale and Jamba 1.5 Mini?

DeepSeek-V3.2-Speciale supports 131K tokens and Jamba 1.5 Mini 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 DeepSeek-V3.2-Speciale and Jamba 1.5 Mini?

Key differences include context window (131K vs 256K), input pricing ($0.28 vs $0.20/M), licensing (MIT vs Jamba Open Model License). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2-Speciale and Jamba 1.5 Mini?

DeepSeek-V3.2-Speciale is developed by DeepSeek and Jamba 1.5 Mini is developed by AI21 Labs.

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