Compare the best 75 chart question answering models and try them on your own images, free in the Roboflow Playground. 26 are open-weight, so you can self-host them for free under their licenses.
75 models · 26 open-weight · 75 free to try · prices synced Sep 11, 2026
We haven't benchmarked chart question answering yet; scores and rankings appear on this site only where we've measured them. Until then, compare the models below, and for fixed categories in production expect a model fine-tuned on your own data to win.
26 models with downloadable weights you can self-host under their licenses (MIT, Apache 2.0, and Modified MIT). All run live in the Playground through hosted APIs, so self-hosting is optional.
| Actions | ||||
|---|---|---|---|---|
GLM 5.3 FlashZ.ai | 320B total, 18B active | MIT | Aug 2026 | |
Qwen3.8 27BQwen | 27.78B | Apache 2.0 | Aug 2026 | |
Muse Glimmer 30BMeta | 29.6B | Apache 2.0 | Aug 2026 | |
Kimi K3Moonshot AI | 2.8T | Modified MIT | Jul 2026 | |
Qwen3.6 27BQwen | 27B | Apache 2.0 | Apr 2026 | |
Qwen3.6 35B A3BQwen | 35B total, 3B active | Apache 2.0 | Apr 2026 | |
Gemma 4 26B A4BGoogle | 25.2B | Apache 2.0 | Apr 2026 | |
Gemma 4 31BGoogle | 31B | Apache 2.0 | Apr 2026 | |
GLM-OCRZ.ai | 0.9B | MIT | Mar 2026 | |
Qwen3.5 9bQwen | 9B | Apache 2.0 | Mar 2026 | |
| 122B | Apache 2.0 | Feb 2026 | ||
Qwen3.5 35B A3BQwen | 35B | Apache 2.0 | Feb 2026 | |
Qwen3.5-27BQwen | 27B | Apache 2.0 | Feb 2026 | |
| 397B | Apache 2.0 | Feb 2026 | ||
Kimi K2.5Moonshot AI | 1T | Modified MIT | Jan 2026 | |
| 8.8B | Apache 2.0 | Oct 2025 | ||
| 31B | Apache 2.0 | Oct 2025 | ||
| 235B | Apache 2.0 | Sep 2025 | ||
Llama 4 MaverickMeta | 400B | Custom | Apr 2025 | |
Llama 4 ScoutMeta | 109B | Custom | Apr 2025 | |
Mistral Small 3.1 24BMistral | 24B | Apache 2.0 | Mar 2025 | |
Gemma 3 12BGoogle | 12B | Custom | Mar 2025 | |
Gemma 3 27BGoogle | — | Custom | Mar 2025 | |
Gemma 3 4BGoogle | 4B | Custom | Mar 2025 | |
| 7B | Apache 2.0 | Jan 2025 | ||
Pixtral 12BMistral | 12B | Apache 2.0 | Sep 2024 |
49 proprietary models where the weights aren't downloadable: access is through each provider's API and billed by them. Try all of them free in the Playground.
| Actions | |||||
|---|---|---|---|---|---|
GPT-6 AstraOpenAI NEW | $10.00 | $50.00 | 1.1M | Sep 2026 | |
Gemini 3.8 FlashGoogle NEW | $0.75 | $3.75 | 1.0M | Sep 2026 | |
Muse Spark 1.3Meta NEW | $1.25 | $4.25 | 1.0M | Sep 2026 | |
Claude Fable 5.1Anthropic NEW | $10.00 | $50.00 | 1M | Sep 2026 | |
Qwen3.8 FlashQwen | $0.15 | $0.47 | 1M | Aug 2026 | |
Gemini 3.7 FlashGoogle | $0.75 | $3.75 | 1.0M | Aug 2026 | |
Grok 4.6SpaceXAI | $2.00 | $6.00 | 500K | Aug 2026 | |
Muse Spark 1.2Meta | $1.25 | $4.25 | 1.0M | Aug 2026 | |
Qwen3.8 MaxQwen | — | — | 984K | Aug 2026 | |
Qwen3.7 FlashQwen | $0.030 | $0.13 | 1M | Jul 2026 | |
Claude Opus 5Anthropic | $5.00 | $25.00 | 1M | Jul 2026 | |
Gemini 3.5 Flash-LiteGoogle | $0.30 | $2.50 | 1.0M | Jul 2026 | |
Gemini 3.6 FlashGoogle | $0.75 | $3.75 | 1M | Jul 2026 | |
GPT-5.6 LunaOpenAI | $0.20 | $1.20 | 1.5M | Jul 2026 | |
GPT-5.6 SolOpenAI | $2.00 | $10.00 | 1.5M | Jul 2026 | |
GPT-5.6 TerraOpenAI | $2.00 | $12.00 | 1.1M | Jul 2026 | |
Muse Spark 1.1Meta | $1.25 | $4.25 | 1.0M | Jul 2026 | |
Grok 4.5SpaceXAI | $2.00 | $6.00 | 500K | Jul 2026 | |
Claude Sonnet 5Anthropic | $2.00 | $10.00 | 1M | Jun 2026 | |
Claude Fable 5Anthropic | $10.00 | $50.00 | 1M | Jun 2026 | |
Claude Opus 4.8Anthropic | $5.00 | $25.00 | 1M | May 2026 | |
Gemini 3.5 FlashGoogle | $1.50 | $9.00 | 1.0M | May 2026 | |
GPT-5.5OpenAI | $5.00 | $30.00 | 1M | Apr 2026 | |
Claude Opus 4.7Anthropic | $5.00 | $25.00 | 1M | Apr 2026 | |
Qwen3.6 FlashQwen | $0.19 | $1.13 | 1M | Apr 2026 | |
Qwen3.6 PlusQwen | $0.33 | $1.95 | 1M | Apr 2026 | |
GLM 5V TurboZ.ai | $1.20 | $4.00 | 200K | Apr 2026 | |
GPT-5.4 MiniOpenAI | $0.75 | $4.50 | 400K | Mar 2026 | |
GPT-5.4 NanoOpenAI | $0.20 | $1.25 | 400K | Mar 2026 | |
GPT-5.4OpenAI | $2.50 | $15.00 | 1.1M | Mar 2026 | |
Gemini 3.1 Flash-LiteGoogle | $0.25 | $1.50 | 1M | Mar 2026 | |
Gemini 3.1 ProGoogle | $2.00 | $12.00 | 1M | Feb 2026 | |
Claude Sonnet 4.6Anthropic | $3.00 | $15.00 | 1M | Feb 2026 | |
Claude Opus 4.6 Anthropic | $5.00 | $25.00 | 1M | Feb 2026 | |
Gemini 3 FlashGoogle | $0.50 | $3.00 | 1M | Dec 2025 | |
GPT-5.2OpenAI | $1.75 | $14.00 | 400K | Dec 2025 | |
Claude Opus 4.5Anthropic | $5.00 | $25.00 | 200K | Nov 2025 | |
GPT-5.1OpenAI | $1.25 | $10.00 | 196K | Nov 2025 | |
Claude Haiku 4.5Anthropic | $1.00 | $5.00 | 200K | Oct 2025 | |
Claude Sonnet 4.5Anthropic | $3.00 | $15.00 | 200K | Sep 2025 | |
Mistral Medium 3.1Mistral | $0.40 | $2.00 | 128K | Aug 2025 | |
GPT-5OpenAI | $1.25 | $10.00 | — | Aug 2025 | |
GPT-5 MiniOpenAI | $0.25 | $2.00 | 400K | Aug 2025 | |
GPT-5 NanoOpenAI | $0.050 | $0.40 | 400K | Aug 2025 | |
Gemini 2.5 Flash-LiteGoogle | $0.10 | $0.40 | 1M | Jul 2025 | |
Gemini 2.5 FlashGoogle | $0.30 | $2.50 | 1M | Jul 2025 | |
Grok 4SpaceXAI | — | — | — | Jul 2025 | |
Gemini 2.5 ProGoogle | $1.25 | $10.00 | 1M | Jun 2025 | |
Qwen VL MaxQwen | — | — | — | Feb 2025 |
Charts encode data in axes, scales, and marks, so answering questions about them means inverting the visualization and then reasoning over numbers, which is exactly where models still make confident mistakes.
The strongest general VLMs read common chart types well: values, comparisons, trends. Reliability drops on dense, small-text, or unconventional charts, and errors are silent, so spot-check against source data before automating anything that matters.
If the underlying table exists, querying it directly (or having a model extract the table first, then compute) beats asking questions of the rendered pixels. Treat chart QA as the fallback for when the image is truly all you have: screenshots, PDFs, legacy reports.
The bottom line: Use a frontier VLM for chart questions, verify on your own charts, and whenever the source data is available, query the data instead of the picture.
Chart question answering is the task of answering questions about charts and plots: reading values, comparing series, and describing trends. Unlike natural photos, charts encode data in axes, scales, legends, and geometric marks, so a model must effectively invert the visualization back into numbers and then reason over them, often requiring arithmetic. Benchmarks like ChartQA score exact answers, and dense or cluttered charts remain a known weak spot even for frontier models. It is used to automate business intelligence review, audit report figures, and make dashboards queryable in plain language. This page lists 75 chart question answering models, including 26 open-weight options you can self-host; all of them run live in the Playground so you can test them on your own images.
It depends on your task and constraints. For fixed categories in production, a model fine-tuned on your own data typically beats any general-purpose model. Compare the chart question answering models on this page and try them on your own images to see which fits.
Yes. 26 of the 75 chart question answering models here are open-weight (for example GLM 5.3 Flash, Qwen3.8 27B, and Muse Glimmer 30B), free to self-host under their licenses (MIT, Apache 2.0, and Modified MIT).
Yes. You can run all 75 in the Roboflow Playground for free. Upload an image and compare the models' output side by side, no setup required.
This page lists all 75 chart question answering models in the Roboflow Playground catalog: 26 open-weight models you can self-host and 49 proprietary models accessed through provider APIs; all of them run live in the Roboflow Playground on your own images. Compare licenses, parameters, API prices, and release dates side by side, or open any model page for full details.