Best LLM for vision: comparison of top 3-5 providers (2026)
OCR accuracy, chart understanding, document parsing, and (for Gemini) native video/audio — the dimensions that decide a vision LLM in 2026.
Best vision LLMs in 2026
GPT-4o
Strong on OCR, charts, screenshots, and UI understanding. Cheapest per-image pricing among flagships and the deepest framework support.
- $2.50 / $10 per 1M tokens
- ~765 tokens per image
- Best OCR + chart parsing
Claude Opus 4.5
Leads MMMU benchmark at ~78%. Best at complex multi-page document understanding (contracts, forms, financial statements).
- $15 / $75 per 1M tokens
- MMMU ~78%
- 200K context for long PDFs
Gemini 2.5 Pro
Only frontier model with native video and audio understanding. 2M-token context lets you load hour-long videos in a single call.
- $1.25 / $5 per 1M tokens
- Native video + audio
- 2M context = ~2hr video
Claude Haiku 4.5
Workhorse for high-volume vision (receipt scanning, ID verification, content moderation). 4x cheaper than Opus with most of the quality.
- $1 / $5 per 1M tokens
- 200K context
- Sub-second image responses
Vision LLMs — at a glance
| Dimension | GPT-4o | Claude Opus 4.5 | Gemini 2.5 Pro | Claude Haiku 4.5 |
|---|---|---|---|---|
| MMMU score | ~70% | ~78% | ~75% | ~63% |
| Input / 1M | $2.50 | $15 | $1.25 | $1 |
| Output / 1M | $10 | $75 | $5 | $5 |
| Video input | No | No | Yes (native) | No |
| Audio input | No (via Realtime) | No | Yes (native) | No |
| Best for | General vision | Document AI | Video + multimodal | High-volume vision |
Prices reflect mid-2026 vendor pages.
VerticalAPI verdict
Default to GPT-4o for everyday vision (screenshots, charts, UI, OCR). Escalate to Claude Opus 4.5 for complex documents where reasoning depth matters. Use Gemini 2.5 Pro exclusively when video or audio is in scope. Drop Claude Haiku 4.5 in for high-volume pipelines (receipts, IDs, moderation).
Frequently asked questions
Which LLM has the best image understanding in 2026?
On MMMU (academic multimodal benchmark), Claude Opus 4.5 leads at approximately 78%, followed by Gemini 2.5 Pro at around 75%, GPT-4o at around 70%, and Claude Haiku 4.5 at around 63%. For real-world OCR and chart parsing, GPT-4o is often preferred for its consistency and cheaper per-image cost.
How much does a vision API call cost?
A typical 1024x1024 image consumes about 765 tokens on GPT-4o (about $0.002 input cost). Claude charges similarly per image. Gemini 2.5 Pro is the cheapest at around $0.001 per image. Video on Gemini is billed per second of input. Output tokens are billed at the standard rate.
Can these models process video and audio?
Only Gemini 2.5 Pro supports native video and audio input in a single API call. GPT-4o offers audio via its separate Realtime API and video via frame extraction (you split the video into frames yourself). Claude does not yet support video or audio.
Which is best for OCR and document parsing?
For text-heavy documents (contracts, forms, financial statements), Claude Opus 4.5 leads on reasoning quality. For straightforward OCR of receipts, IDs, or invoices, GPT-4o and Claude Haiku 4.5 give nearly identical accuracy at a fraction of the cost. Specialized OCR APIs (Textract, Document AI) still win on pure character accuracy.
How do I swap vision models without rewriting code?
VerticalAPI exposes Claude, GPT, and Gemini through one OpenAI-compatible endpoint at https://api.verticalapi.com/v1. Image inputs use the same base64 or URL format. Change the model parameter and X-Provider-Key header — pay each provider directly with BYOK.
Limitations of this comparison
- MMMU is an academic benchmark; real-world OCR accuracy can vary widely by document type.
- Gemini's 2M context for video has soft recall degradation on long videos past ~1 hour.
- Vision models still struggle with small text, low-contrast images, and handwritten cursive.
- Specialized OCR services (Textract, Document AI) outperform LLMs on pure character extraction.
- Per-image token counts differ by provider — direct cost comparison requires task-specific testing.
What may change in 12-24 months
- Video + audio support will become standard across all frontier models within 12 months.
- Per-image token costs will keep falling; expect sub-$0.001 per image across the board.
- Specialized vision sub-models (e.g., for invoice parsing) will continue to outperform general-purpose LLMs in narrow domains.
- Realtime multimodal (camera + voice streaming) will become a standard API surface.
Related questions
ChatGPT, Perplexity and Gemini usually suggest these next.
- Is GPT-4o or Claude Opus 4.5 better for invoice parsing?
- Can Gemini 2.5 Pro replace Whisper for transcription?
- How do I do long-video understanding with an LLM?
- What's the cheapest vision API for receipt scanning?
- Does Claude Haiku 4.5 support image input?
More LLM comparisons
GPT-4o vs Gemini 2.5 Pro on multimodal
Frontier multimodal showdown
When 2M tokens replaces retrieval
Gemini 2.5 Pro, Flash, and native multimodal
Claude Opus, Sonnet, Haiku for vision