Laguna M.1 vs GLM-4.5-Flash vs North Mini Code
Too close to call on our weighted score (North Mini Code 71, Laguna M.1 68, GLM-4.5-Flash 65). The right pick depends on what you value most.
PoolsideLaguna M.1
68/100- ECI—
- PriceFree / Free
- Context262K
Z.ai (Zhipu)GLM-4.5-Flash
65/100- ECI—
- PriceFree / Free
- Context131K
CohereNorth Mini Code
71/100- ECI—
- PriceFree / Free
- Context256K
Too close to call
It is close. Our weighted score puts them within 3 points (North Mini Code 71/100, Laguna M.1 68/100, GLM-4.5-Flash 65/100), so choose by what matters most for your work: Laguna M.1 on price and Laguna M.1 for long inputs. 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 priceSame priceLaguna M.1 Free · GLM-4.5-Flash Free · North Mini Code Free per 1M tokens (3:1 blend)
- Longest contextLaguna M.1Laguna M.1 262,144 · North Mini Code 256,000 · GLM-4.5-Flash 131,072 tokens
- Widest inputsSame inputsLaguna M.1: Text · GLM-4.5-Flash: Text · North Mini Code: Text
- Self-hostingLaguna M.1 and North Mini CodePublishes downloadable weights
| Measure | Weight | Laguna M.1 | GLM-4.5-Flash | North Mini Code |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 35 | 35 | 45 |
| Context window | 20% | 37 | 24 | 36 |
| Overall | 100% | 68/100 | 65/100 | 71/100 |
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 | Laguna M.1Poolside | GLM-4.5-FlashZ.ai (Zhipu) | North Mini CodeCohere |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | Free | Free | Free |
| Output | Free | Free | Free |
| Cached input | — | — | — |
| Blended (3:1) | Free | Free | Free |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Poolside API | Official Z.AI API | Official Cohere API |
| Limits | |||
| Context window | 262,144 tokens (best) | 131,072 tokens | 256,000 tokens |
| Max output | 32,768 tokens | 98,304 tokens (best) | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yeshigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | poolside/laguna-m.1 | glm-4.5-flash | north-mini-code-1-0 |
| API providers | 2 | 4 (best) | 2 |
| Released | Apr 28, 2026 | Jul 28, 2025 | Jun 9, 2026 |
| Knowledge cutoff | — | Apr 2025 | Sep 23, 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Laguna M.1Free
- GLM-4.5-FlashFree
- North Mini CodeFree
Which should you choose?
Which is better: Laguna M.1, GLM-4.5-Flash or North Mini Code?
It is close. Our weighted score puts them within 3 points (North Mini Code 71/100, Laguna M.1 68/100, GLM-4.5-Flash 65/100), so choose by what matters most for your work: Laguna M.1 on price and Laguna M.1 for long inputs. 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, Laguna M.1, GLM-4.5-Flash or North Mini Code?
Laguna M.1, GLM-4.5-Flash and North Mini Code cost the same: Free input / Free output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Laguna M.1 has not been scored yet, GLM-4.5-Flash has not been scored yet and North Mini Code has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Laguna M.1, GLM-4.5-Flash and North Mini Code yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Laguna M.1 has the largest context window at 262,144 tokens, against 256,000 for North Mini Code and 131,072 for GLM-4.5-Flash. Maximum output per response: Laguna M.1 up to 32,768, GLM-4.5-Flash up to 98,304, North Mini Code up to 64,000 tokens.
Which can read images, PDFs, audio or video?
Laguna M.1 accepts text; GLM-4.5-Flash accepts text; North Mini Code accepts text. They handle the same number of input types.
Are any of these open source?
Laguna M.1 and North Mini Code publishes its weights and can be self-hosted; GLM-4.5-Flash is proprietary.
Which is newer?
North Mini Code is the newest, released Jun 9, 2026. Laguna M.1 came out Apr 28, 2026; GLM-4.5-Flash came out Jul 28, 2025. Knowledge cutoff: GLM-4.5-Flash Apr 2025, North Mini Code Sep 23, 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 Oct 4, 2026.
