Antigravity Agent vs GLM OCR

This comparison does not currently contain a protocol-matched coding benchmark for both Antigravity Agent and GLM OCR, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.

Antigravity Agent has the larger sourced context window. Antigravity Agent supports 1,049K and GLM OCR supports 131K.

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

GLM OCR is the only model in this pair currently marked as self-hostable. Antigravity Agent is not marked open weight; GLM OCR is open weight.

Antigravity Agent is documented with image input; GLM OCR is documented with image input. This reflects supported input modalities, not vision quality.

Neither has a larger sourced maximum output. Antigravity Agent is 66K and GLM OCR is —.

Antigravity Agent: reasoning, tool calling, and image input. GLM OCR: tool calling and image input. Feature support does not establish relative quality.

Antigravity Agent has 2 sourced provider routes; GLM OCR has 1, so Antigravity Agent has broader tracked availability.

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.