GLM-4.6 vs Ling-1T vs Ling 3.1 Flash
Ling 3.1 Flash comes out ahead, 65 to 42 and 37 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)
GLM-4.6
42/100- ECI—
- Price$0.60 / $2.20
- Context205K
inclusionAI
Ling-1T
37/100- ECI—
- Price$0.57 / $2.29
- Context128K
- Our pick
inclusionAI
Ling 3.1 Flash
65/100- ECI—
- Price$0.075 / $0.22
- Context262K
Ling 3.1 Flash is our pick
Ling 3.1 Flash is the better all-round choice, scoring 65/100 against GLM-4.6 (42) and Ling-1T (37). It leads on price 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 priceLing 3.1 FlashLing 3.1 Flash $0.111 · GLM-4.6 $1.00 · Ling-1T $1.00 per 1M tokens (3:1 blend)
- Longest contextLing 3.1 FlashLing 3.1 Flash 262,144 · GLM-4.6 204,800 · Ling-1T 128,000 tokens
- Widest inputsSame inputsGLM-4.6: Text · Ling-1T: Text · Ling 3.1 Flash: Text
- Self-hostingGLM-4.6 and Ling-1TPublishes downloadable weights
| Measure | Weight | GLM-4.6 | Ling-1T | Ling 3.1 Flash |
|---|---|---|---|---|
| Price | 50% | 50 | 50 | 95 |
| Inputs & features | 30% | 35 | 25 | 35 |
| Context window | 20% | 32 | 24 | 37 |
| Overall | 100% | 42/100 | 37/100 | 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 | $0.60 | $0.57 | $0.075 (best) |
| Output | $2.20 | $2.29 | $0.22 (best) |
| Cached input | $0.11 | — | — |
| Blended (3:1) | $1.00 | $1.00 | $0.111 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Bailing API | Median of 1 providers |
| Limits | |||
| Context window | 204,800 tokens | 128,000 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 32,000 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 | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | glm-4.6 | Ling-1T | — |
| API providers | 18 (best) | 1 | 3 |
| Released | Sep 30, 2025 | Oct 2025 | Sep 29, 2026 |
| Knowledge cutoff | Apr 2025 | Jun 2024 | — |
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
Ling-1T$10.28
Ling 3.1 Flash$1.19
Which should you choose?
Which is better: GLM-4.6, Ling-1T or Ling 3.1 Flash?
Ling 3.1 Flash is the better all-round choice, scoring 65/100 against GLM-4.6 (42) and Ling-1T (37). It leads on price 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, GLM-4.6, Ling-1T or Ling 3.1 Flash?
Ling 3.1 Flash is cheaper at $0.075 input / $0.22 output per million tokens (median across 1 API provider). GLM-4.6 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price); Ling-1T costs $0.57 input / $2.29 output per million tokens (official Bailing API price). At a typical mix of three input tokens to one output token, that is $0.111 per million tokens for Ling 3.1 Flash versus $1.00 for GLM-4.6 (9× as much) and $1.00 for Ling-1T (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, Ling-1T has not been scored yet and Ling 3.1 Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.6, Ling-1T and Ling 3.1 Flash 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?
Ling 3.1 Flash has the largest context window at 262,144 tokens, against 204,800 for GLM-4.6 and 128,000 for Ling-1T. Maximum output per response: GLM-4.6 up to 131,072, Ling-1T up to 32,000, Ling 3.1 Flash up to 32,768 tokens.
Which can read images, PDFs, audio or video?
GLM-4.6 accepts text; Ling-1T accepts text; Ling 3.1 Flash accepts text. They handle the same number of input types.
Are any of these open source?
GLM-4.6 and Ling-1T publishes its weights and can be self-hosted; Ling 3.1 Flash is proprietary.
Which is newer?
Ling 3.1 Flash is the newest, released Sep 29, 2026. Ling-1T came out Oct 2025; GLM-4.6 came out Sep 30, 2025. Knowledge cutoff: GLM-4.6 Apr 2025, Ling-1T Jun 2024.
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.