Qwen3 Coder Next Base 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

FieldQwen3-Coder-Next-BaseBonsai 1.7B
DeveloperQwenPrismML
FamilyQwen3 Coder Next BaseBonsai 1 7b
ModelQwen3-Coder-Next-BaseBonsai 1.7B
VersionQwen3-Coder-Next-BaseBonsai 1.7B
Lifecycleactiveactive
ReleasedUnknown2026-03-29
Knowledge cutoffUnknownUnknown
Input modalitiesTextText
Output modalitiesTextText
Context window262K33K
Total parameters79.7B1.7B
Active parameters3BUnknown
Licenseapache-2.0apache-2.0
Open weightsYesYes
API availableUnknownNo
Self-hostableYesYes
Provider accessUnknownUnknown
Capabilitieschat, generation, toolschat, generation
Effective bit widthUnknown1 bit per weight
Weight sizeUnknown0.25 GB
Weight formatUnknownBinary Q1_0

Qwen3 Coder Next Base Capabilities

chatgenerationtools
Serving providers0
Canonical IDQwen/Qwen3-Coder-Next-Base

Bonsai 1.7B Capabilities

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

Primary Evidence

Sources and Freshness

Questions

Qwen3 Coder Next Base vs Bonsai 1.7B FAQs

Is Qwen3 Coder Next Base or Bonsai 1.7B better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3 Coder Next Base and Bonsai 1.7B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Qwen3 Coder Next Base 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, Qwen3 Coder Next Base or Bonsai 1.7B?+

Qwen3 Coder Next Base has the larger sourced context window. Qwen3 Coder Next Base supports 262K and Bonsai 1.7B supports 33K.

Which performs better in benchmarks, Qwen3 Coder Next Base 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 Qwen3 Coder Next Base or Bonsai 1.7B be self-hosted?+

Both models have the same recorded self-hosting status: supported. Qwen3 Coder Next Base is open weight; Bonsai 1.7B is open weight.

Can Qwen3 Coder Next Base and Bonsai 1.7B understand images?+

Qwen3 Coder Next Base is not 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, Qwen3 Coder Next Base or Bonsai 1.7B?+

Neither has a larger sourced maximum output. Qwen3 Coder Next Base is — and Bonsai 1.7B is —.

Do Qwen3 Coder Next Base and Bonsai 1.7B support reasoning and tool use?+

Qwen3 Coder Next Base: tool calling. Bonsai 1.7B: none of these features are definitively sourced. Feature support does not establish relative quality.

Which is available from more inference providers, Qwen3 Coder Next Base or Bonsai 1.7B?+

Qwen3 Coder Next Base has 0 sourced provider routes; Bonsai 1.7B has 0, a tie.

Which offers better value, Qwen3 Coder Next Base 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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