Live pricing on OneInfer
Pulled from the OneInfer catalog (OpenRouter and direct provider routes) at request time — rates can change. Capture the timestamp with any benchmark or production decision.
| Model | Provider | Input $/1M tokens | Output $/1M tokens |
|---|---|---|---|
| GLM-5.3-Flash | zai | $140.00 | $440.00 |
| GLM-5.3-Flash | zai | $100.00 | $320.00 |
| GLM-5.3-Flash | zai | $7.50 | $25.00 |
| GLM-5.3-Flash | novita | $7.50 | $25.00 |
| GLM-5.3-Flash | together_ai | $15.00 | $50.00 |
| Claude Opus 4.8 | anthropic | $500.00 | $2500.00 |
Decision snapshot
| Decision factor | GLM-5.3-Flash | Claude Opus 4.8 |
|---|---|---|
| Text and agent workflows | High-volume flash tier, multimodal input, low per-token cost | Closed frontier — pick when measured reasoning depth beats price |
| Input price per 1M tokens | $0.075 | $15.00 |
| Output price per 1M tokens | $0.250 | $75.00 |
| Context window | 1,048,576 tokens | 200,000 tokens |
| Input modalities | Text, image, video, file | Text and images |
| Architecture | Mixture-of-experts | Closed (Anthropic) |
| License | Z.ai proprietary | Proprietary, managed APIs |
| Deployment control | API; weights pending release | Managed APIs only; no self-host option |
| Vendor | Z.ai | Anthropic |
How to read this comparison
Z.ai's positioning for GLM-5.3-Flash against Claude Opus 4.8 is volume and openness, not parity on reasoning depth. The honest framing: Opus 4.8 sits on Anthropic's closed frontier with measured independent gains, and GLM-5.3-Flash is a multimodal flash tier at roughly 1/200th the input price and 1/300th the output price. The workload — not the headline — decides whether that gap is worth closing.
Pricing context
Opus 4.8 lists at $15.00 input / $75.00 output per 1M tokens on the OneInfer pricing facet — about 200× GLM-5.3-Flash on input and 300× on output. At a 1:3 input:output ratio, GLM-5.3-Flash blends to ~$0.21 per 1M tokens versus Opus 4.8 at ~$45.00. The comparison is honest about that gap: the closed frontier commands a real premium, not a marginal one.
Ready to test the workflow?
Create account & add creditsStrengths and tradeoffs
GLM-5.3-Flash wins on price, multimodal breadth (text + image + video + file), and 1M-token context. Claude Opus 4.8 wins on measured frontier reasoning quality, image input at frontier depth, and a managed API posture that simplifies compliance for workloads that prefer a single-vendor SLA. Both serve image input; GLM-5.3-Flash adds video and file; Opus 4.8 stays on the harder reasoning rows.
Workload recommendation
| Workload | Recommended starting point |
|---|---|
| High-volume routing, classification, extraction | GLM-5.3-Flash |
| Frontier reasoning where the cost of being wrong is the dominant expense | Claude Opus 4.8 |
| Multimodal document Q&A (image, video, file) | GLM-5.3-Flash |
| Image-only input at the hardest reasoning tier | Claude Opus 4.8 |
| Long-context analysis (>200K tokens) | GLM-5.3-Flash |
| Managed single-vendor SLA with compliance simplicity | Claude Opus 4.8 |
Frequently asked questions
Is Claude Opus 4.8 cheaper than GLM-5.3-Flash?
No. Opus 4.8 lists at $15.00 input / $75.00 output per 1M tokens — about 200× more expensive on input and 300× on output than GLM-5.3-Flash ($0.075 / $0.250). The closed-frontier premium is real, not marginal.
Is Claude Opus 4.8 multimodal?
Opus 4.8 supports text and image input. GLM-5.3-Flash adds video and file on top of that, at a fraction of the price.
Which should I use when the workload is hardest?
Validate on your prompt set. The closed frontier has measured reasoning gains, but the gap is workload-specific and the price difference is large enough that even a small accuracy win needs to clear a real cost bar.
Can I try GLM-5.3 before integrating it?
Use the OneInfer GLM-5.3 launcher to open a prepared prompt in the authenticated playground. Availability is checked against the current model catalog.
How should I treat benchmark claims?
Check the provenance label and harness version. Vendor-reported and independently verified results are deliberately shown as different evidence classes.
Put GLM-5.3 to work
Fund a controlled evaluation, start with a prepared prompt, and measure quality and cost on your own workload.