GLM-4.5-Flash vs Laguna XS 2.1 vs North Mini Code
Too close to call on our weighted score (Laguna XS 2.1 68, North Mini Code 68, GLM-4.5-Flash 65). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-4.5-Flash
65/100- ECI—
- PriceFree / Free
- Context131K
PoolsideLaguna XS 2.1
68/100- ECI—
- PriceFree / Free
- Context262K
CohereNorth Mini Code
68/100- ECI—
- PriceFree / Free
- Context256K
Too close to call
It is close. Our weighted score puts them within a point (Laguna XS 2.1 68/100, North Mini Code 68/100, GLM-4.5-Flash 65/100), so choose by what matters most for your work: GLM-4.5-Flash on price and Laguna XS 2.1 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 priceGLM-4.5-Flash Free · Laguna XS 2.1 Free · North Mini Code Free per 1M tokens (3:1 blend)
- Longest contextLaguna XS 2.1Laguna XS 2.1 262,144 · North Mini Code 256,000 · GLM-4.5-Flash 131,072 tokens
- Widest inputsSame inputsGLM-4.5-Flash: Text · Laguna XS 2.1: Text · North Mini Code: Text
- Self-hostingLaguna XS 2.1 and North Mini CodePublishes downloadable weights
| Measure | Weight | GLM-4.5-Flash | Laguna XS 2.1 | North Mini Code |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 35 | 35 | 35 |
| Context window | 20% | 25 | 37 | 36 |
| Overall | 100% | 65/100 | 68/100 | 68/100 |
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 | GLM-4.5-FlashZ.ai (Zhipu) | Laguna XS 2.1Poolside | 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 Z.AI API | Official Poolside API | Official Cohere API |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens (best) | 256,000 tokens |
| Max output | 98,304 tokens (best) | 32,768 tokens | 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 | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | glm-4.5-flash | poolside/laguna-xs-2.1 | north-mini-code-1-0 |
| API providers | 5 (best) | 3 | 4 |
| Released | Jul 28, 2025 | Jul 2, 2026 | 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.
- GLM-4.5-FlashFree
- Laguna XS 2.1Free
- North Mini CodeFree
Which should you choose?
Which is better: GLM-4.5-Flash, Laguna XS 2.1 or North Mini Code?
It is close. Our weighted score puts them within a point (Laguna XS 2.1 68/100, North Mini Code 68/100, GLM-4.5-Flash 65/100), so choose by what matters most for your work: GLM-4.5-Flash on price and Laguna XS 2.1 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, GLM-4.5-Flash, Laguna XS 2.1 or North Mini Code?
GLM-4.5-Flash, Laguna XS 2.1 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. GLM-4.5-Flash has not been scored yet, Laguna XS 2.1 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 GLM-4.5-Flash, Laguna XS 2.1 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 XS 2.1 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: GLM-4.5-Flash up to 98,304, Laguna XS 2.1 up to 32,768, North Mini Code up to 64,000 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Flash accepts text; Laguna XS 2.1 accepts text; North Mini Code accepts text. They handle the same number of input types.
Are any of these open source?
Laguna XS 2.1 and North Mini Code publishes its weights and can be self-hosted; GLM-4.5-Flash is proprietary.
Which is newer?
Laguna XS 2.1 is the newest, released Jul 2, 2026. North Mini Code came out Jun 9, 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 Nov 2, 2026.
