Databricks: Models Intelligence, Performance & Price
Analysis of Databricks's models across key metrics including quality, price, output speed, latency, context window & more. This analysis is intended to support you in choosing the best model provided by Databricks for your use-case.
(te)
Most Intelligent
Intelligence index
Total 2 models
Fastest
Output speed
Total 2 models
Lowest Price
Blended price (per 1M tokens)
Total 2 models
Databricks offers 2 models, each with different intelligence, performance, and pricing characteristics. Below is a comparison of the key metrics across models.
- For intelligence, the top models on Databricks are Kimi K3 (max) (60) and GLM-5.2 (max) (53).
- For output speed, the fastest models are Kimi K3 (max) (119 t/s) and GLM-5.2 (max) (101 t/s).
- For latency, Kimi K3 (max) (18.15s) and GLM-5.2 (max) (20.84s) offer the lowest time to first answer token.
- For pricing, GLM-5.2 (max) ($0.90) and Kimi K3 (max) ($2.31) offer the lowest blended prices per 1M tokens.
- For context window size, GLM-5.2 (max) (1M) and Kimi K3 (max) (205k) support the largest context windows on Databricks.
- Kimi K3 (max) offers the best combination of intelligence and speed. For cost optimization, GLM-5.2 (max) provides the most competitive pricing.
Highlights
Intelligence Evaluations
Artificial Analysis Intelligence Index
Intelligence Evaluations
Agentic real-world work tasks, (Elo-500)/2000
Agentic tool use
Agentic coding & terminal use
Coding
Reasoning & knowledge
Scientific reasoning
Physics reasoning
Knowledge
1 - hallucination rate
Long context reasoning
Agentic knowledge work, Elo
Agentic SaaS workflows
Legal agentic work, criterion pass rate
Agentic business operations
Quantitative analysis on spreadsheets & documents
Instruction following
Long-horizon agentic tasks
Kubernetes incident root-cause analysis
Visual reasoning
Intelligence Index vs. Price
Context Window
Context Window
Pricing
Intelligence Index vs. Price
Performance Summary
Output Speed vs. Price
Speed
Measured by Output Speed (tokens per second)
Output Speed
Latency
Measured by Time (seconds) to First Token
Latency: Time To First Answer Token
End-to-End Response Time
Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed
End-to-End Response Time vs. Price
Key definitions
Frequently Asked Questions
Common questions about Databricks
Databricks offers 2 models that we track: Kimi K3 (max) and GLM-5.2 (max).
The most intelligent model available on Databricks is Kimi K3 (max) with an Intelligence Index score of 60.
The fastest model on Databricks by output speed is Kimi K3 (max) at 118.6 tokens per second.
The model with the lowest time to first answer token on Databricks is Kimi K3 (max) at 18.15s. Lower latency means faster initial response time.
The most affordable model on Databricks by blended price is GLM-5.2 (max) at $0.90 per 1M tokens (7:2:1 cache hit/input/output ratio).
Prices on Databricks vary up to 3x across models, from $0.90 per 1M tokens for GLM-5.2 (max) to $2.31 per 1M tokens for Kimi K3 (max).
Yes, Databricks offers an OpenAI-compatible API, making it easy to switch from OpenAI or use existing OpenAI SDK integrations.
Yes, all 2 models on Databricks support JSON mode for structured output.
Yes, all 2 models on Databricks support function calling (tool use).
Yes, Databricks offers 2 reasoning models: Kimi K3 (max) and GLM-5.2 (max). Reasoning models use extended thinking to work through complex problems before providing an answer.
Yes, all 2 models on Databricks are open weight models.
Yes, provider performance can vary over time due to infrastructure changes, load balancing, and updates. We continuously benchmark all providers and display historical performance trends in the "Over Time" charts.
When choosing a model on Databricks, consider: intelligence (for quality-sensitive tasks), output speed (for throughput-intensive tasks), latency (for interactive applications requiring quick first responses), pricing (for cost-sensitive workloads), and features like context window size, JSON mode, or function calling support.