AutoGLM Phone 9B Multilingual vs Granite-4.0-H-Micro vs Trinity Mini
Too close to call on our weighted score (Trinity Mini 65, Granite-4.0-H-Micro 62, AutoGLM Phone 9B Multilingual 60). The right pick depends on what you value most.
Z.ai (Zhipu)AutoGLM Phone 9B Multilingual
60/100- ECI—
- Price$0.035 / $0.138
- Context66K
IBMGranite-4.0-H-Micro
62/100- ECI—
- Price$0.018 / $0.115
- Context131K
Arcee AITrinity Mini
65/100- ECI—
- Price$0.045 / $0.15
- Context131K
Too close to call
It is close. Our weighted score puts them within 3 points (Trinity Mini 65/100, Granite-4.0-H-Micro 62/100, AutoGLM Phone 9B Multilingual 60/100), so choose by what matters most for your work: Granite-4.0-H-Micro on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGranite-4.0-H-MicroGranite-4.0-H-Micro $0.042 · AutoGLM Phone 9B Multilingual $0.061 · Trinity Mini $0.071 per 1M tokens (3:1 blend)
- Longest contextGranite-4.0-H-Micro and Trinity MiniGranite-4.0-H-Micro 131,072 · Trinity Mini 131,072 · AutoGLM Phone 9B Multilingual 65,536 tokens
- Widest inputsAutoGLM Phone 9B MultilingualAutoGLM Phone 9B Multilingual: Text, Images · Granite-4.0-H-Micro: Text · Trinity Mini: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | AutoGLM Phone 9B Multilingual | Granite-4.0-H-Micro | Trinity Mini |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 25 | 25 | 35 |
| Context window | 20% | 12 | 25 | 25 |
| Overall | 100% | 60/100 | 62/100 | 65/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | AutoGLM Phone 9B MultilingualZ.ai (Zhipu) | Granite-4.0-H-MicroIBM | Trinity MiniArcee AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.035 | $0.018 (best) | $0.045 |
| Output | $0.138 | $0.115 (best) | $0.15 |
| Cached input | — | — | — |
| Blended (3:1) | $0.061 | $0.042 (best) | $0.071 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 2 providers | Median of 1 providers |
| Limits | |||
| Context window | 65,536 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Max output | 65,536 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenMIT | Open | OpenOpenMDW-1.1 |
| API model ID | — | — | — |
| API providers | 2 (best) | 2 (best) | 1 |
| Released | Dec 10, 2025 | Oct 2, 2025 | Dec 1, 2025 |
| Knowledge cutoff | — | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- AutoGLM Phone 9B Multilingual$0.626
- Granite-4.0-H-Micro$0.405
- Trinity Mini$0.75
Which should you choose?
Which is better: AutoGLM Phone 9B Multilingual, Granite-4.0-H-Micro or Trinity Mini?
It is close. Our weighted score puts them within 3 points (Trinity Mini 65/100, Granite-4.0-H-Micro 62/100, AutoGLM Phone 9B Multilingual 60/100), so choose by what matters most for your work: Granite-4.0-H-Micro on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, AutoGLM Phone 9B Multilingual, Granite-4.0-H-Micro or Trinity Mini?
Granite-4.0-H-Micro is cheaper at $0.018 input / $0.115 output per million tokens (median across 2 API providers). AutoGLM Phone 9B Multilingual costs $0.035 input / $0.138 output per million tokens (median across 2 API providers); Trinity Mini costs $0.045 input / $0.15 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.042 per million tokens for Granite-4.0-H-Micro versus $0.061 for AutoGLM Phone 9B Multilingual (1.5× as much) and $0.071 for Trinity Mini (1.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. AutoGLM Phone 9B Multilingual has not been scored yet, Granite-4.0-H-Micro has not been scored yet and Trinity Mini has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for AutoGLM Phone 9B Multilingual, Granite-4.0-H-Micro and Trinity Mini yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that AutoGLM Phone 9B Multilingual does not support tool calling, which most coding agents need.
Which has the bigger context window?
Granite-4.0-H-Micro and Trinity Mini have the largest context windows (131,072 and 131,072 tokens), against 65,536 for AutoGLM Phone 9B Multilingual. Maximum output per response: AutoGLM Phone 9B Multilingual up to 65,536, Granite-4.0-H-Micro up to 131,072, Trinity Mini up to 131,072 tokens.
Which can read images, PDFs, audio or video?
AutoGLM Phone 9B Multilingual accepts text and images; Granite-4.0-H-Micro accepts text; Trinity Mini accepts text. AutoGLM Phone 9B Multilingual handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (MIT and OpenMDW-1.1), so you can self-host them.
Which is newer?
AutoGLM Phone 9B Multilingual is the newest, released Dec 10, 2025. Trinity Mini came out Dec 1, 2025; Granite-4.0-H-Micro came out Oct 2, 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
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