Ternary Bonsai 27B vs GLM 5.3 Flash
At a Glance
| Compare |  Ternary Bonsai 27BPrismML |  GLM 5.3 FlashZ.ai |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #29 of 4654.6 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 36.4–69.8 |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #2 of 44$0.0087 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #1 of 3877.3 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 68.2–84.9 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.075Z.ai ↗ · Aug 29, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $0.25Z.ai ↗ · Aug 29, 2026 |
| Context windowMaximum documented tokens | 262K | 1,000K |
| Model facts checked | Sep 18, 2026View model evidence → | Sep 2, 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
Side-by-Side Facts
| Field | Ternary Bonsai 27B | GLM-5.3-Flash |
|---|---|---|
| Developer | PrismML | Z.ai |
| Family | Bonsai 27b | Glm 5 3 Flash |
| Model | Ternary Bonsai 27B | GLM-5.3-Flash |
| Version | Ternary Bonsai 27B | GLM-5.3-Flash |
| Lifecycle | active | active |
| Released | 2026-07-04 | 2026-09-02 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image, Video, Document |
| Output modalities | Text | Text |
| Context window | 262K | 1,000K |
| Total parameters | 27B | 320B |
| Active parameters | Unknown | 18B |
| License | apache-2.0 | MIT |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Together Ai (Standard) | Deepinfra (Standard), Fireworks Ai (Standard), Together Ai (Standard), Z.ai (Standard) |
| Capabilities | chat, generation, reasoning, tools, vision | agents, chat, computer-use, reasoning, structured_outputs, tools, vision |
| Base model | Qwen3.6 27B | Unknown |
| Effective bit width | 1.58 bits per weight | Unknown |
| Language model size | 6.66 GiB | Unknown |
| Weight format | Ternary Q2_0 | Unknown |
Ternary Bonsai 27B Capabilities
GLM 5.3 Flash Capabilities
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Primary Evidence
Sources and Freshness
Questions
Ternary Bonsai 27B vs GLM 5.3 Flash FAQs
Is Ternary Bonsai 27B or GLM 5.3 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Ternary Bonsai 27B and GLM 5.3 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Ternary Bonsai 27B or GLM 5.3 Flash?+
Only GLM 5.3 Flash has a directly sourced input price: $0.075 per million tokens. Only GLM 5.3 Flash has a directly sourced output price: $0.25 per million tokens.
Which has a larger context window, Ternary Bonsai 27B or GLM 5.3 Flash?+
GLM 5.3 Flash has the larger sourced context window. Ternary Bonsai 27B supports 262K and GLM 5.3 Flash supports 1,000K.
Which performs better in benchmarks, Ternary Bonsai 27B or GLM 5.3 Flash?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Ternary Bonsai 27B or GLM 5.3 Flash be self-hosted?+
Both models have the same recorded self-hosting status: supported. Ternary Bonsai 27B is open weight; GLM 5.3 Flash is open weight.
Can Ternary Bonsai 27B and GLM 5.3 Flash understand images?+
Ternary Bonsai 27B is documented with image input; GLM 5.3 Flash is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Ternary Bonsai 27B or GLM 5.3 Flash?+
Neither has a larger sourced maximum output. Ternary Bonsai 27B is — and GLM 5.3 Flash is 131K.
Do Ternary Bonsai 27B and GLM 5.3 Flash support reasoning and tool use?+
Ternary Bonsai 27B: reasoning, tool calling, and image input. GLM 5.3 Flash: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Ternary Bonsai 27B or GLM 5.3 Flash?+
Ternary Bonsai 27B has 1 sourced provider route; GLM 5.3 Flash has 4, so GLM 5.3 Flash has broader tracked availability.
Which offers better value, Ternary Bonsai 27B or GLM 5.3 Flash?+
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.