GLM-5 vs Inkling
GLM-5 and Inkling are closely matched at 36.8 and 37.1 on the LLM Stats Score. GLM-5 is 1.1x cheaper per token.
Zhipu AI · Thinking Machines Lab · Updated for 2026
Which is better?
GLM-5 and Inkling are closely matched on the overall LLM Stats Score at 36.8 and 37.1.
The models split the 2 individual benchmarks reported for both models evenly.
On price, GLM-5 is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Inkling also accepts a larger context window (524,288 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GLM-5
- cost matters — it's about 1.1x cheaper per token
Choose Inkling
- you process long inputs — it offers a 524,288 token context window
- you want the most recent training data — it shipped Jul 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for GLM-5 · 16 for Inkling
GLM-5 outperforms in 1 benchmarks (SWE-Bench Verified), while Inkling is better at 1 benchmark (MCP Atlas).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5 ($1.00/1M tokens) is 1.1x more expensive than Inkling ($0.95/1M tokens).
For output processing, GLM-5 ($3.20/1M tokens) is 1.3x cheaper than Inkling ($4.05/1M tokens).
In conclusion, Inkling is more expensive than GLM-5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Inkling has 231.0B more parameters than GLM-5, making it 31.0% larger.
Context Window
Maximum input and output token capacity
Inkling accepts 524,288 input tokens compared to GLM-5's 200,000 tokens. Inkling can generate longer responses up to 524,288 tokens, while GLM-5 is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Inkling supports multimodal inputs, whereas GLM-5 does not.
Inkling can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5
Inkling
License
Usage and distribution terms
GLM-5 is licensed under MIT, while Inkling uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
GLM-5 was released on 2026-02-11, while Inkling was released on 2026-07-21.
Inkling is 5 months newer than GLM-5.
Feb 11, 2026
8 months ago
Jul 21, 2026
3 months ago
5mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5 is available from FriendliAI, ZAI. Inkling is available from DeepInfra.
GLM-5
Inkling
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5 and Inkling side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5 vs Inkling.