Simon Willison’s Weblog

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Thursday, 25th September 2025

If you hide the system prompt and tool descriptions for your LLM agent, what you're actually doing is deliberately hiding the most useful documentation describing your service from your most sophisticated users!

# 12:24 am / ai-agents, llms, ai, generative-ai

Improved Gemini 2.5 Flash and Flash-Lite (via) Two new preview models from Google - updates to their fast and inexpensive Flash and Flash Lite families:

The latest version of Gemini 2.5 Flash-Lite was trained and built based on three key themes:

  • Better instruction following: The model is significantly better at following complex instructions and system prompts.
  • Reduced verbosity: It now produces more concise answers, a key factor in reducing token costs and latency for high-throughput applications (see charts above).
  • Stronger multimodal & translation capabilities: This update features more accurate audio transcription, better image understanding, and improved translation quality.

[...]

This latest 2.5 Flash model comes with improvements in two key areas we heard consistent feedback on:

  • Better agentic tool use: We've improved how the model uses tools, leading to better performance in more complex, agentic and multi-step applications. This model shows noticeable improvements on key agentic benchmarks, including a 5% gain on SWE-Bench Verified, compared to our last release (48.9% → 54%).
  • More efficient: With thinking on, the model is now significantly more cost-efficient—achieving higher quality outputs while using fewer tokens, reducing latency and cost (see charts above).

They also added two new convenience model IDs: gemini-flash-latest and gemini-flash-lite-latest, which will always resolve to the most recent model in that family.

I released llm-gemini 0.26 adding support for the new models and new aliases. I also used the response.set_resolved_model() method added in LLM 0.27 to ensure that the correct model ID would be recorded for those -latest uses.

llm install -U llm-gemini

Both of these models support optional reasoning tokens. I had them draw me pelicans riding bicycles in both thinking and non-thinking mode, using commands that looked like this:

llm -m gemini-2.5-flash-preview-09-2025 -o thinking_budget 4000 "Generate an SVG of a pelican riding a bicycle"

I then got each model to describe the image it had drawn using commands like this:

llm -a https://static.simonwillison.net/static/2025/gemini-2.5-flash-preview-09-2025-thinking.png -m gemini-2.5-flash-preview-09-2025 -o thinking_budget 2000 'Detailed single line alt text for this image'

gemini-2.5-flash-preview-09-2025-thinking

A minimalist stick figure graphic depicts a person with a white oval body and a dot head cycling a gray bicycle, carrying a large, bright yellow rectangular box resting high on their back.

gemini-2.5-flash-preview-09-2025

A simple cartoon drawing of a pelican riding a bicycle, with the text "A Pelican Riding a Bicycle" above it.

gemini-2.5-flash-lite-preview-09-2025-thinking

A quirky, simplified cartoon illustration of a white bird with a round body, black eye, and bright yellow beak, sitting astride a dark gray, two-wheeled vehicle with its peach-colored feet dangling below.

gemini-2.5-flash-lite-preview-09-2025

A minimalist, side-profile illustration of a stylized yellow chick or bird character riding a dark-wheeled vehicle on a green strip against a white background.

# 7:27 pm / google, llms, llm, gemini, pelican-riding-a-bicycle, llm-reasoning, llm-release

2025 » September

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