GLM-5.3-Flash vs GLM-4.7-FlashX
GLM-5.3-Flash comes out ahead, 79 to 61 on our weighted score, though GLM-4.7-FlashX is 36% cheaper per token.
- Our pick
Z.ai (Zhipu)GLM-5.3-Flash
79/100- ECI151.9
- Price$0.15 / $0.50
- Context1M
- Z.ai (Zhipu)
GLM-4.7-FlashX
61/100- ECI—
- Price$0.07 / $0.40
- Context200K
Add a model
Make it a three-way comparison.
GLM-5.3-Flash is our pick
GLM-5.3-Flash is the better all-round choice, scoring 79/100 against GLM-4.7-FlashX (61). It leads on inputs & features and context window. GLM-4.7-FlashX wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGLM-4.7-FlashXGLM-4.7-FlashX $0.152 · GLM-5.3-Flash $0.237 per 1M tokens (3:1 blend)
- Longest contextGLM-5.3-FlashGLM-5.3-Flash 1,000,000 · GLM-4.7-FlashX 200,000 tokens
- Widest inputsGLM-5.3-FlashGLM-5.3-Flash: Text, Images, PDFs, Video · GLM-4.7-FlashX: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-5.3-Flash | GLM-4.7-FlashX |
|---|---|---|---|
| Price | 50% | 79 | 89 |
| Inputs & features | 30% | 90 | 35 |
| Context window | 20% | 60 | 32 |
| Overall | 100% | 79/100 | 61/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.3-FlashZ.ai (Zhipu) | GLM-4.7-FlashXZ.ai (Zhipu) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 151.9 | — |
| ECI rank | #42 of 148 | — |
| GPQA DiamondGraduate-level science questions | 90.2% | — |
| FrontierMath Tiers 1–3Research-level mathematics | 55.8% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.9% | — |
| Price per million tokens | ||
| Input | $0.15 | $0.07 (best) |
| Output | $0.50 | $0.40 (best) |
| Cached input | $0.03 | $0.01 (best) |
| Blended (3:1) | $0.237 | $0.152 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Z.AI API |
| Limits | ||
| Context window | 1,000,000 tokens (best) | 200,000 tokens |
| Max output | 131,072 tokens | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | Yes | No |
| Audio | No | No |
| Video | Yes | No |
| Reasoning | Yeslow · high · max | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | glm-5.3-flash | glm-4.7-flashx |
| API providers | 65 (best) | 8 |
| Released | Aug 26, 2026 | Jan 19, 2026 |
| Knowledge cutoff | — | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5.3-Flash$2.50
- GLM-4.7-FlashX$1.50
Which should you choose?
Which is better: GLM-5.3-Flash or GLM-4.7-FlashX?
GLM-5.3-Flash is the better all-round choice, scoring 79/100 against GLM-4.7-FlashX (61). It leads on inputs & features and context window. GLM-4.7-FlashX wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, GLM-5.3-Flash or GLM-4.7-FlashX?
GLM-4.7-FlashX is cheaper at $0.07 input / $0.40 output per million tokens (official Z.AI API price). GLM-5.3-Flash costs $0.15 input / $0.50 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.152 per million tokens for GLM-4.7-FlashX versus $0.237 for GLM-5.3-Flash (1.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-5.3-Flash has an ECI of 151.9 and GLM-4.7-FlashX has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3-Flash and GLM-4.7-FlashX yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
GLM-5.3-Flash has the largest context window at 1,000,000 tokens, against 200,000 for GLM-4.7-FlashX. Maximum output per response: GLM-5.3-Flash up to 131,072, GLM-4.7-FlashX up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3-Flash accepts text, images, PDFs and video; GLM-4.7-FlashX accepts text. GLM-5.3-Flash handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
GLM-5.3-Flash is the newest, released Aug 26, 2026. GLM-4.7-FlashX came out Jan 19, 2026. Knowledge cutoff: GLM-4.7-FlashX Apr 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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