AI model comparison
GLM 4.7 Flash vs gpt-oss-120b
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
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.
- Input / 1M
- $0.06
- Output / 1M
- $0.40
- Context
- 200K
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.
- Input / 1M
- $0.15
- Output / 1M
- $0.60
- Context
- 131K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
GLM 4.7 Flash
1.9x cheaper for a typical chat
Higher intelligence score
GLM 4.7 Flash
14.9 vs 11.6 on Artificial Analysis
Larger context window
GLM 4.7 Flash
200K vs 131K tokens
Newer release
GLM 4.7 Flash
Released January 19, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
GLM 4.7 Flash vs gpt-oss-120b API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.06 | $0.15 |
| Output tokensPer 1M tokens | $0.40 | $0.60 |
| Cached input (read)Per 1M tokens | Not available | $0.08 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 200K tokens | 131K tokens |
| Max output | 118K tokens | 66K tokens |
| Input types | Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | High, Medium, Low |
| Default reasoning effort | Not available | Medium |
| Release date | January 19, 2026 | August 5, 2025 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Our take
GLM 4.7 Flash is 1.9x cheaper for a typical chat. GLM 4.7 Flash scores higher on the Artificial Analysis Intelligence Index (14.9 vs 11.6). GLM 4.7 Flash has the larger context window (200K vs 131K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is GLM 4.7 Flash or gpt-oss-120b cheaper?
GLM 4.7 Flash is cheaper for a typical chat (2K input tokens and 500 output tokens). GLM 4.7 Flash costs $0.06 per 1M input tokens and $0.40 per 1M output tokens, while gpt-oss-120b costs $0.15 per 1M input tokens and $0.60 per 1M output tokens.
Which has a bigger context window, GLM 4.7 Flash or gpt-oss-120b?
GLM 4.7 Flash supports up to 200K tokens of context, compared with 131K for gpt-oss-120b.
Is GLM 4.7 Flash smarter than gpt-oss-120b?
On the Artificial Analysis Intelligence Index, GLM 4.7 Flash scores 14.9 and gpt-oss-120b scores 11.6, putting GLM 4.7 Flash ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use GLM 4.7 Flash and gpt-oss-120b at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see GLM 4.7 Flash and gpt-oss-120b answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to GLM 4.7 Flash and gpt-oss-120b at the same time. Compare the answers side by side and keep the best one.