AutoGLM Phone 9B Multilingual vs LFM2 24B A2B vs Trinity Mini
Trinity Mini comes out ahead, 65 to 60 and 58 on our weighted score, though LFM2 24B A2B is 26% cheaper per token.
Z.ai (Zhipu)
AutoGLM Phone 9B Multilingual
60/100- ECI—
- Price$0.035 / $0.138
- Context66K
Liquid AI
LFM2 24B A2B
58/100- ECI—
- Price$0.03 / $0.12
- Context33K
- Our pick
Arcee AI
Trinity Mini
65/100- ECI—
- Price$0.045 / $0.15
- Context131K
Trinity Mini is our pick
Trinity Mini is the better all-round choice, scoring 65/100 against AutoGLM Phone 9B Multilingual (60) and LFM2 24B A2B (58). It leads on inputs & features and context window. 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 priceLFM2 24B A2BLFM2 24B A2B $0.052 · AutoGLM Phone 9B Multilingual $0.061 · Trinity Mini $0.071 per 1M tokens (3:1 blend)
- Longest contextTrinity MiniTrinity Mini 131,072 · AutoGLM Phone 9B Multilingual 65,536 · LFM2 24B A2B 32,768 tokens
- Widest inputsAutoGLM Phone 9B MultilingualAutoGLM Phone 9B Multilingual: Text, Images · LFM2 24B A2B: 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 | LFM2 24B A2B | Trinity Mini |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 25 | 25 | 35 |
| Context window | 20% | 12 | 0 | 25 |
| Overall | 100% | 60/100 | 58/100 | 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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.035 | $0.03 (best) | $0.045 |
| Output | $0.138 | $0.12 (best) | $0.15 |
| Cached input | — | — | — |
| Blended (3:1) | $0.061 | $0.052 (best) | $0.071 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 1 providers | Median of 1 providers |
| Limits | |||
| Context window | 65,536 tokens | 32,768 tokens | 131,072 tokens (best) |
| Max output | 65,536 tokens | 32,768 tokens | 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 | OpenLFM Open License v1.0 | OpenOpenMDW-1.1 |
| API model ID | — | — | — |
| API providers | 2 (best) | 1 | 1 |
| Released | Dec 10, 2025 | Feb 24, 2026 | 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
LFM2 24B A2B$0.54
Trinity Mini$0.75
Which should you choose?
Which is better: AutoGLM Phone 9B Multilingual, LFM2 24B A2B or Trinity Mini?
Trinity Mini is the better all-round choice, scoring 65/100 against AutoGLM Phone 9B Multilingual (60) and LFM2 24B A2B (58). It leads on inputs & features and context window. 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, LFM2 24B A2B or Trinity Mini?
LFM2 24B A2B is cheaper at $0.03 input / $0.12 output per million tokens (median across 1 API provider). 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 $0.052 per million tokens for LFM2 24B A2B versus $0.061 for AutoGLM Phone 9B Multilingual (1.2× as much) and $0.071 for Trinity Mini (1.4× 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, LFM2 24B A2B 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, LFM2 24B A2B 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?
Trinity Mini has the largest context window at 131,072 tokens, against 65,536 for AutoGLM Phone 9B Multilingual and 32,768 for LFM2 24B A2B. Maximum output per response: AutoGLM Phone 9B Multilingual up to 65,536, LFM2 24B A2B up to 32,768, Trinity Mini up to 131,072 tokens.
Which can read images, PDFs, audio or video?
AutoGLM Phone 9B Multilingual accepts text and images; LFM2 24B A2B 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, LFM Open License v1.0 and OpenMDW-1.1), so you can self-host them.
Which is newer?
LFM2 24B A2B is the newest, released Feb 24, 2026. AutoGLM Phone 9B Multilingual came out Dec 10, 2025; Trinity Mini came out Dec 1, 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.