Mistral Medium 3.5 128B vs Bonsai 1.7B

At a Glance

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Pricing and Limits
Context windowMaximum documented tokens262K33K
Model facts checkedAug 28, 2026View model evidence →Sep 18, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldMistral-Medium-3.5-128BBonsai 1.7B
DeveloperMistral AIPrismML
FamilyMistral Medium 3 5 128bBonsai 1 7b
ModelMistral-Medium-3.5-128BBonsai 1.7B
VersionMistral-Medium-3.5-128BBonsai 1.7B
Lifecycleactiveactive
ReleasedUnknown2026-03-29
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText
Output modalitiesTextText
Context window262K33K
Total parameters127.7B1.7B
Active parametersUnknownUnknown
Licenseotherapache-2.0
Open weightsYesYes
API availableUnknownNo
Self-hostableYesYes
Provider accessUnknownUnknown
Capabilitieschat, generation, reasoning, toolschat, generation
Effective bit widthUnknown1 bit per weight
Weight sizeUnknown0.25 GB
Weight formatUnknownBinary Q1_0

Mistral Medium 3.5 128B Capabilities

chatgenerationreasoningtools
Serving providers0
Canonical IDmistralai/Mistral-Medium-3.5-128B

Bonsai 1.7B Capabilities

chatgeneration
Serving providers0
Canonical IDprism-ml/Bonsai-1.7B

Primary Evidence

Sources and Freshness

Questions

Mistral Medium 3.5 128B vs Bonsai 1.7B FAQs

Is Mistral Medium 3.5 128B or Bonsai 1.7B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Mistral Medium 3.5 128B and Bonsai 1.7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Mistral Medium 3.5 128B or Bonsai 1.7B?+

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

Which has a larger context window, Mistral Medium 3.5 128B or Bonsai 1.7B?+

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

Which performs better in benchmarks, Mistral Medium 3.5 128B or Bonsai 1.7B?+

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

Can Mistral Medium 3.5 128B or Bonsai 1.7B be self-hosted?+

Both models have the same recorded self-hosting status: supported. Mistral Medium 3.5 128B is open weight; Bonsai 1.7B is open weight.

Can Mistral Medium 3.5 128B and Bonsai 1.7B understand images?+

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

Which can generate longer answers, Mistral Medium 3.5 128B or Bonsai 1.7B?+

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

Do Mistral Medium 3.5 128B and Bonsai 1.7B support reasoning and tool use?+

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

Which is available from more inference providers, Mistral Medium 3.5 128B or Bonsai 1.7B?+

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

Which offers better value, Mistral Medium 3.5 128B or Bonsai 1.7B?+

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.

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