Mistral Medium 3.5 128B vs Ternary Bonsai 1.7B

This comparison does not currently contain a protocol-matched coding benchmark for both Mistral Medium 3.5 128B and Ternary Bonsai 1.7B, 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.

Mistral Medium 3.5 128B has the larger sourced context window. Mistral Medium 3.5 128B supports 262K and Ternary Bonsai 1.7B supports 33K.

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. Mistral Medium 3.5 128B is open weight; Ternary Bonsai 1.7B is open weight.

Mistral Medium 3.5 128B is documented with image input; Ternary Bonsai 1.7B is not documented with image input. This reflects supported input modalities, not vision quality.

Neither has a larger sourced maximum output. Mistral Medium 3.5 128B is — and Ternary Bonsai 1.7B is —.

Mistral Medium 3.5 128B: reasoning, tool calling, and image input. Ternary Bonsai 1.7B: none of these features are definitively sourced. Feature support does not establish relative quality.

Mistral Medium 3.5 128B has 0 sourced provider routes; Ternary Bonsai 1.7B has 0, a tie.

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.