Model comparison
gpt-oss-120b vs GLM 4.7 Flash
Price history, scores and specs for both models, line by line. Every value shows where it came from and when we last confirmed it.
OpenAI
gpt-oss-120b
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases.
Z Ai
GLM 4.7 Flash
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency.
Quick take
Where each one leads
- GLM 4.7 Flash costs less to send text to: $0.060 per million tokens, against $0.150 per million tokens for gpt-oss-120b.
- GLM 4.7 Flash costs less per word it writes: $0.400 per million tokens, against $0.600 per million tokens for gpt-oss-120b.
- GLM 4.7 Flash reads more at once: 200,000 tokens, against 131,072 tokens.
- GLM 4.7 Flash scores higher on the Artificial Analysis Intelligence Index: 14.9 to 3.8.
- More people run gpt-oss-120b through OpenRouter than GLM 4.7 Flash right now.
Each line comes from a checked value in the tables below. Pick on your workload: price and usage matter for high volume, context and scores for long documents and agent loops.
Price history
Prices side by side, day by day
- gpt-oss-120b
- GLM 4.7 Flash
- gpt-oss-120b
- GLM 4.7 Flash
Prices are the listed OpenRouter base rates in US dollars. A day we could not confirm is left out of the line, never filled in.
Price
What each one costs now
| Measure | gpt-oss-120b | GLM 4.7 Flash |
|---|---|---|
| Input price | $0.150 per million tokens | $0.060 per million tokens Leads |
| Output price | $0.600 per million tokens | $0.400 per million tokens Leads |
Scores
Benchmarks, with source and date
| Measure | gpt-oss-120b | GLM 4.7 Flash |
|---|---|---|
| Artificial Analysis Intelligence Index | 3.8 | 14.9 Leads |
| Artificial Analysis Coding Index | 30.4 | Not checked yet |
| Artificial Analysis Agentic Index | 3.7 | Not checked yet |
| LMArena text rating (Elo) | 1,365 Leads | 1,351 |
| Design Arena rating (Elo) | 986 | 1,202 Leads |
Specs
Context, modalities and tool use
| Measure | gpt-oss-120b | GLM 4.7 Flash |
|---|---|---|
| Context window | 131,072 tokens | 200,000 tokens Leads |
| Reads | Text | Text |
| Writes | Text | Text |
| Tool calling | Yes | Yes |
| Reasoning mode | Yes | Yes |
| Open weights | Yes | Yes |
| Listed since | 5 Aug 2025 | 19 Jan 2026 |
Usage
How much each one is used
| Measure | gpt-oss-120b | GLM 4.7 Flash |
|---|---|---|
| Tokens served on OpenRouter in a day | 69B Leads (for 10 Nov 2026) | 1.3B (for 10 Nov 2026) |
| Requests on OpenRouter in a day | 18.3M Leads (for 10 Nov 2026) | 845K (for 10 Nov 2026) |
| Tool calls on OpenRouter in a day | 761.8K Leads (for 10 Nov 2026) | 51.9K (for 10 Nov 2026) |
| Token usage, last 7 days | Up 2% on the week before Leads (for 10 Nov 2026) | Down 19% on the week before (for 10 Nov 2026) |
- gpt-oss-120b
- GLM 4.7 Flash
How this works
One link, either order
This link stays the same whichever order you name the two models in, so you can share it as it is. A line appears only when at least one model has a value we confirmed from a source; values we have not confirmed are left out, never guessed. To add a third record of any type, use the open comparison. Read how we check facts.