GLM-4.6 vs Laguna S 2.1 vs Ling 3.0 Flash Fin
Laguna S 2.1 comes out ahead, 69 to 65 and 42 on our weighted score, though Ling 3.0 Flash Fin is 11% cheaper per token.
Z.ai (Zhipu)GLM-4.6
42/100- ECI—
- Price$0.60 / $2.20
- Context205K
- Our pick
PoolsideLaguna S 2.1
69/100- ECI—
- Price$0.10 / $0.20
- Context1.05M
inclusionAILing 3.0 Flash Fin
65/100- ECI—
- Price$0.075 / $0.22
- Context262K
Laguna S 2.1 is our pick
Laguna S 2.1 is the better all-round choice, scoring 69/100 against Ling 3.0 Flash Fin (65) and GLM-4.6 (42). It leads on context window. Ling 3.0 Flash Fin wins 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 priceLing 3.0 Flash FinLing 3.0 Flash Fin $0.111 · Laguna S 2.1 $0.125 · GLM-4.6 $1.00 per 1M tokens (3:1 blend)
- Longest contextLaguna S 2.1Laguna S 2.1 1,048,576 · Ling 3.0 Flash Fin 262,144 · GLM-4.6 204,800 tokens
- Widest inputsSame inputsGLM-4.6: Text · Laguna S 2.1: Text · Ling 3.0 Flash Fin: Text
- Self-hostingGLM-4.6 and Laguna S 2.1Publishes downloadable weights
| Measure | Weight | GLM-4.6 | Laguna S 2.1 | Ling 3.0 Flash Fin |
|---|---|---|---|---|
| Price | 50% | 50 | 93 | 95 |
| Inputs & features | 30% | 35 | 35 | 35 |
| Context window | 20% | 32 | 61 | 37 |
| Overall | 100% | 42/100 | 69/100 | 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 | GLM-4.6Z.ai (Zhipu) | Laguna S 2.1Poolside | Ling 3.0 Flash FininclusionAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.60 | $0.10 | $0.075 (best) |
| Output | $2.20 | $0.20 (best) | $0.22 |
| Cached input | $0.11 | — | — |
| Blended (3:1) | $1.00 | $0.125 | $0.111 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 4 providers | Median of 1 providers |
| Limits | |||
| Context window | 204,800 tokens | 1,048,576 tokens (best) | 262,144 tokens |
| Max output | 131,072 tokens (best) | 32,768 tokens | 32,768 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 | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.6 | poolside/laguna-s-2.1 | — |
| API providers | 18 (best) | 6 | 2 |
| Released | Sep 30, 2025 | Jul 21, 2026 | Aug 27, 2026 |
| Knowledge cutoff | Apr 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-4.6$10.40
- Laguna S 2.1$1.40
- Ling 3.0 Flash Fin$1.19
Which should you choose?
Which is better: GLM-4.6, Laguna S 2.1 or Ling 3.0 Flash Fin?
Laguna S 2.1 is the better all-round choice, scoring 69/100 against Ling 3.0 Flash Fin (65) and GLM-4.6 (42). It leads on context window. Ling 3.0 Flash Fin wins 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, GLM-4.6, Laguna S 2.1 or Ling 3.0 Flash Fin?
Ling 3.0 Flash Fin is cheaper at $0.075 input / $0.22 output per million tokens (median across 1 API provider). Laguna S 2.1 costs $0.10 input / $0.20 output per million tokens (median across 4 API providers; free on Poolside); GLM-4.6 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.111 per million tokens for Ling 3.0 Flash Fin versus $0.125 for Laguna S 2.1 (1.1× as much) and $1.00 for GLM-4.6 (9× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.6 has not been scored yet, Laguna S 2.1 has not been scored yet and Ling 3.0 Flash Fin has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.6, Laguna S 2.1 and Ling 3.0 Flash Fin 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 S 2.1 has the largest context window at 1,048,576 tokens, against 262,144 for Ling 3.0 Flash Fin and 204,800 for GLM-4.6. Maximum output per response: GLM-4.6 up to 131,072, Laguna S 2.1 up to 32,768, Ling 3.0 Flash Fin up to 32,768 tokens.
Which can read images, PDFs, audio or video?
GLM-4.6 accepts text; Laguna S 2.1 accepts text; Ling 3.0 Flash Fin accepts text. They handle the same number of input types.
Are any of these open source?
GLM-4.6 and Laguna S 2.1 publishes its weights and can be self-hosted; Ling 3.0 Flash Fin is proprietary.
Which is newer?
Ling 3.0 Flash Fin is the newest, released Aug 27, 2026. Laguna S 2.1 came out Jul 21, 2026; GLM-4.6 came out Sep 30, 2025. Knowledge cutoff: GLM-4.6 Apr 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.
