Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1): The Ultimate Performance & Pricing Comparison

Deep dive into reasoning, benchmarks, and latency insights.

The Final Verdict in the Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) Showdown

After a comprehensive analysis, DeepSeek LLM 67B Chat (V1) emerges as the superior choice for users prioritizing raw intelligence and reasoning. However, Kimi Linear 48B A3B Instruct remains a highly competitive option, especially for scenarios demanding faster response times and cost-efficiency. This detailed Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) comparison will break down every critical metric to help you make the best decision.

Explore best-for scenarios•Let the AI Selector recommend next steps

Model Snapshot

Key decision metrics at a glance.

Kimi Linear 48B A3B Instruct

Other

Reasoning: 4
Coding: 1
Multimodal: 1
Long Context: 2
Blended Price / 1M tokens: $0.015
P95 Latency: 1000ms
Tokens per second: —

DeepSeek LLM 67B Chat (V1)

DeepSeek

Reasoning: 6
Coding: 6
Multimodal: 1
Long Context: 1
Blended Price / 1M tokens: $0.015
P95 Latency: 1000ms
Tokens per second: —

Overall Capabilities

The capability radar provides a holistic view of the Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) matchup. This chart illustrates each model's strengths and weaknesses at a glance, forming a cornerstone of our Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) analysis.

This radar chart visually maps the core capabilities (reasoning, coding, math proxy, multimodal, long context) of `Kimi Linear 48B A3B Instruct` vs `DeepSeek LLM 67B Chat (V1)`.

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 Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) debate, Kimi Linear 48B A3B Instruct scores 40 against DeepSeek LLM 67B Chat (V1)'s 60. This data-driven approach is essential for any serious Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) comparison.

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

Speed & Latency

Speed is a crucial factor in the Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) decision for interactive applications. The metrics below highlight the trade-offs you should weigh before shipping to production.

Time to First Token

Kimi Linear 48B A3B Instruct300ms

DeepSeek LLM 67B Chat (V1)300ms

Tokens per Second

Kimi Linear 48B A3B Instruct66

DeepSeek LLM 67B Chat (V1)50

Head to the playground to validate these results yourself

The Economics of Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1)

Power is only one part of the equation. This Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) 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, Kimi Linear 48B A3B Instruct would cost $0.018, whereas DeepSeek LLM 67B Chat (V1) would cost $0.018. This practical calculation is vital for any developer considering the Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) choice.

Review the complete pricing and packaging strategy

Which Model Wins the Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) Battle for You?

Choose Kimi Linear 48B A3B Instruct if...

You need the most advanced reasoning capabilities available.

Your use case demands cutting-edge AI performance.

Choose DeepSeek LLM 67B Chat (V1) if...

You are developing at scale where operational costs are critical.

You prioritize cost-effectiveness over maximum performance.

Your workload requires consistent, reliable performance.

Explore all Best picks Use the AI Selector for a tailored recommendation

Your Questions about the Kimi Linear 48B A3B Instruct vs DeepSeek LLM 67B Chat (V1) Comparison

Review the full evaluation methodology · Read the latest analysis posts

Data source: https://artificialanalysis.ai/