ERNIE X1.1 vs Phi-4 Multimodal Instruct

This comparison does not currently contain a protocol-matched coding benchmark for both ERNIE X1.1 and Phi-4 Multimodal Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Only ERNIE X1.1 has a directly sourced input price: $1.00 per million tokens. Only ERNIE X1.1 has a directly sourced output price: $4.00 per million tokens.

Phi-4 Multimodal Instruct has the larger sourced context window. ERNIE X1.1 supports 66K and Phi-4 Multimodal Instruct supports 131K.

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

Phi-4 Multimodal Instruct is the only model in this pair currently marked as self-hostable. ERNIE X1.1 is not marked open weight; Phi-4 Multimodal Instruct is open weight.

ERNIE X1.1 is not documented with image input; Phi-4 Multimodal Instruct is documented with image input. This reflects supported input modalities, not vision quality.

Neither has a larger sourced maximum output. ERNIE X1.1 is 66K and Phi-4 Multimodal Instruct is —.

ERNIE X1.1: reasoning and tool calling. Phi-4 Multimodal Instruct: image input. Feature support does not establish relative quality.

ERNIE X1.1 has 1 sourced provider route; Phi-4 Multimodal Instruct has 0, so ERNIE X1.1 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.