DeepSeek V4 Pro Base vs GLM 5V Turbo

This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4 Pro Base and GLM 5V Turbo, 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.

DeepSeek V4 Pro Base has the larger sourced context window. DeepSeek V4 Pro Base supports 1,049K and GLM 5V Turbo supports 200K.

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

DeepSeek V4 Pro Base is the only model in this pair currently marked as self-hostable. DeepSeek V4 Pro Base is open weight; GLM 5V Turbo is not marked open weight.

DeepSeek V4 Pro Base is not documented with image input; GLM 5V Turbo is documented with image input. This reflects supported input modalities, not vision quality.

Neither has a larger sourced maximum output. DeepSeek V4 Pro Base is — and GLM 5V Turbo is 131K.

DeepSeek V4 Pro Base: none of these features are definitively sourced. GLM 5V Turbo: reasoning, tool calling, and image input. Feature support does not establish relative quality.

DeepSeek V4 Pro Base has 0 sourced provider routes; GLM 5V Turbo has 1, so GLM 5V Turbo 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.