Jamba 1.7 Large vs Kimi K2 Thinking: The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the Jamba 1.7 Large vs Kimi K2 Thinking Showdown

After a comprehensive analysis, Kimi K2 Thinking emerges as the superior choice for users prioritizing raw intelligence and reasoning. However, Jamba 1.7 Large remains a highly competitive option, especially for scenarios demanding faster response times and cost-efficiency. This detailed Jamba 1.7 Large vs Kimi K2 Thinking comparison will break down every critical metric to help you make the best decision.

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Model Snapshot

Key decision metrics at a glance.

Jamba 1.7 Large

Other

Reasoning: 1
Coding: 1
Multimodal: 1
Long Context: 1
Blended Price / 1M tokens: $0.004
P95 Latency: 1000ms
Tokens per second: 44.612tokens/sec

Kimi K2 Thinking

Other

Reasoning: 9
Coding: 3
Multimodal: 3
Long Context: 5
Blended Price / 1M tokens: $0.001
P95 Latency: 1000ms
Tokens per second: 88.492tokens/sec

Overall Capabilities

The capability radar provides a holistic view of the Jamba 1.7 Large vs Kimi K2 Thinking matchup. This chart illustrates each model's strengths and weaknesses at a glance, forming a cornerstone of our Jamba 1.7 Large vs Kimi K2 Thinking analysis.

This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `Jamba 1.7 Large` vs `Kimi K2 Thinking`.

Benchmark Breakdown

For a granular look, this chart directly compares scores across standardized benchmarks. In the critical MMLU Pro test, a key part of the Jamba 1.7 Large vs Kimi K2 Thinking debate, Jamba 1.7 Large scores 10 against Kimi K2 Thinking's 90. This data-driven approach is essential for any serious Jamba 1.7 Large vs Kimi K2 Thinking comparison.

This grouped bar chart provides a side-by-side comparison for each benchmark metric.

Speed & Latency

Speed is a crucial factor in the Jamba 1.7 Large vs Kimi K2 Thinking decision for interactive applications. The metrics below highlight the trade-offs you should weigh before shipping to production.

Time to First Token

Jamba 1.7 Large300ms

Kimi K2 Thinking300ms

Tokens per Second

Jamba 1.7 Large44.612

Kimi K2 Thinking88.492

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The Economics of Jamba 1.7 Large vs Kimi K2 Thinking

Power is only one part of the equation. This Jamba 1.7 Large vs Kimi K2 Thinking pricing analysis gives you a true sense of value.

Pricing Breakdown

Compare input and output pricing at a glance.

Real-World Cost Scenario

To process 1M input tokens and generate 250k output tokens, Jamba 1.7 Large would cost $0.004, whereas Kimi K2 Thinking would cost $0.001. This practical calculation is vital for any developer considering the Jamba 1.7 Large vs Kimi K2 Thinking choice.

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Which Model Wins the Jamba 1.7 Large vs Kimi K2 Thinking Battle for You?

Choose Jamba 1.7 Large if...

Cost is a secondary concern to power in your Jamba 1.7 Large vs Kimi K2 Thinking decision.

You need the most advanced reasoning capabilities available.

Your use case demands cutting-edge AI performance.

Choose Kimi K2 Thinking if...

You need a highly responsive model for user-facing applications.

Your budget is a primary consideration in the Jamba 1.7 Large vs Kimi K2 Thinking choice.

You are developing at scale where operational costs are critical.

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Your Questions about the Jamba 1.7 Large vs Kimi K2 Thinking Comparison

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Data source: https://artificialanalysis.ai/