GLM-5.3-Flash vs GPT-6.1 Sol
GPT-6.1 Sol leads the LLM Stats Score 54.3 to 49.0. GLM-5.3-Flash is 16.8x cheaper per token.
Zhipu AI · OpenAI · Updated for 2026
Which is better?
GPT-6.1 Sol leads the overall LLM Stats Score 54.3 to 49.0, ranking #5 overall.
In the 1 individual benchmarks reported for both models, GPT-6.1 Sol wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.3-Flash is roughly 16.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6.1 Sol also accepts a larger context window (1,050,000 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-5.3-Flash
- cost matters — it's about 16.8x cheaper per token
- you need open weights you can self-host or fine-tune
Choose GPT-6.1 Sol
- overall performance matters — it scores 54.3 and ranks #5 on LLM Stats
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for GLM-5.3-Flash · 17 for GPT-6.1 Sol
GLM-5.3-Flash outperforms in 0 benchmarks, while GPT-6.1 Sol is better at 1 benchmark (DeepSWE 1.1).
GPT-6.1 Sol significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3-Flash ($0.15/1M tokens) is 13.3x cheaper than GPT-6.1 Sol ($2.00/1M tokens).
For output processing, GLM-5.3-Flash ($0.50/1M tokens) is 20.0x cheaper than GPT-6.1 Sol ($10.00/1M tokens).
In conclusion, GPT-6.1 Sol is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6.1 Sol accepts 1,050,000 input tokens compared to GLM-5.3-Flash's 1,048,576 tokens. GLM-5.3-Flash can generate longer responses up to 1,048,576 tokens, while GPT-6.1 Sol is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GLM-5.3-Flash and GPT-6.1 Sol support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GLM-5.3-Flash
GPT-6.1 Sol
License
Usage and distribution terms
GLM-5.3-Flash is licensed under MIT, while GPT-6.1 Sol uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5.3-Flash was released on 2026-08-26, while GPT-6.1 Sol was released on 2026-09-29.
GPT-6.1 Sol is 1 month newer than GLM-5.3-Flash.
Aug 26, 2026
1 months ago
Sep 29, 2026
1 weeks ago
1mo newerKnowledge Cutoff
When training data ends
GPT-6.1 Sol has a documented knowledge cutoff of 2026-04-30, while GLM-5.3-Flash's cutoff date is not specified.
We can confirm GPT-6.1 Sol's training data extends to 2026-04-30, but cannot make a direct comparison without GLM-5.3-Flash's cutoff date.
—
Apr 2026
Provider Availability
GLM-5.3-Flash is available from DeepInfra, FriendliAI, Novita, ZAI. GPT-6.1 Sol is available from OpenAI.
GLM-5.3-Flash
GPT-6.1 Sol
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3-Flash and GPT-6.1 Sol side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3-Flash vs GPT-6.1 Sol.