DeepSeek-V4-Pro-Base vs Llama-4-Maverick-17B-128E-Instruct

This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek-V4-Pro-Base and Llama-4-Maverick-17B-128E-Instruct, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Only Llama-4-Maverick-17B-128E-Instruct has a directly sourced input price: $0.20 per million tokens. Only Llama-4-Maverick-17B-128E-Instruct has a directly sourced output price: $0.696 per million tokens.

DeepSeek-V4-Pro-Base has the larger sourced context window. DeepSeek-V4-Pro-Base supports 1,048,576 and Llama-4-Maverick-17B-128E-Instruct supports 1,000,000.

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

Both models have the same recorded self-hosting status: supported. DeepSeek-V4-Pro-Base is open weight; Llama-4-Maverick-17B-128E-Instruct is open weight.

DeepSeek-V4-Pro-Base is not documented with image input; Llama-4-Maverick-17B-128E-Instruct 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 Llama-4-Maverick-17B-128E-Instruct is —.

DeepSeek-V4-Pro-Base: none of these features are definitively sourced. Llama-4-Maverick-17B-128E-Instruct: tool calling and image input. Feature support does not establish relative quality.

DeepSeek-V4-Pro-Base has 0 sourced provider routes; Llama-4-Maverick-17B-128E-Instruct has 1, so Llama-4-Maverick-17B-128E-Instruct 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.