GLM-5.3-Flash vs DeepSeek V4.1 Flash 1017
Too close to call on our weighted score (GLM-5.3-Flash 79, DeepSeek V4.1 Flash 1017 79). The right pick depends on what you value most.
Z.ai (Zhipu)GLM-5.3-Flash
79/100- ECI153.2
- Price$0.15 / $0.50
- Context1M
DeepSeekDeepSeek V4.1 Flash 1017
79/100- ECI158.8
- Price$0.15 / $0.60
- Context1M
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within a point (GLM-5.3-Flash 79/100, DeepSeek V4.1 Flash 1017 79/100), so choose by what matters most for your work: DeepSeek V4.1 Flash 1017 for raw capability and GLM-5.3-Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek V4.1 Flash 1017Capabilities Index (ECI): DeepSeek V4.1 Flash 1017 158.8 · GLM-5.3-Flash 153.2
- Lowest priceGLM-5.3-FlashGLM-5.3-Flash $0.237 · DeepSeek V4.1 Flash 1017 $0.263 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGLM-5.3-Flash 1,000,000 · DeepSeek V4.1 Flash 1017 1,000,000 tokens
- Widest inputsGLM-5.3-FlashGLM-5.3-Flash: Text, Images, PDFs, Video · DeepSeek V4.1 Flash 1017: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | GLM-5.3-Flash | DeepSeek V4.1 Flash 1017 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 80 | 87 |
| Price | 25% | 76 | 74 |
| Inputs & features | 15% | 90 | 70 |
| Context window | 10% | 60 | 60 |
| Overall | 100% | 79/100 | 79/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.3-FlashZ.ai (Zhipu) | DeepSeek V4.1 Flash 1017DeepSeek |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 153.2 | 158.8 (best) |
| ECI rank | #48 of 165 | #19 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 90.2% | 93.2% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 55.8% | 71.2% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.9% | 99.4% (best) |
| SimpleQA VerifiedShort factual questions | — | 42.5% |
| Price per million tokens | ||
| Input | $0.15 | $0.15 |
| Output | $0.50 (best) | $0.60 |
| Cached input | $0.03 | $0.003 (best) |
| Blended (3:1) | $0.237 (best) | $0.263 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official DeepSeek API |
| Limits | ||
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 131,072 tokens | 384,000 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | No |
| Audio | No | No |
| Video | Yes | No |
| Reasoning | Yeslow · high · max | Yeslow · high · max |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Open | OpenMIT |
| API model ID | glm-5.3-flash | deepseek-flash |
| API providers | 80 (best) | 40 |
| Released | Aug 26, 2026 | Oct 17, 2026 |
| Knowledge cutoff | — | May 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
- DeepSeek V4.1 Flash 1017$2.70
Which should you choose?
Which is better: GLM-5.3-Flash or DeepSeek V4.1 Flash 1017?
It is close. Our weighted score puts them within a point (GLM-5.3-Flash 79/100, DeepSeek V4.1 Flash 1017 79/100), so choose by what matters most for your work: DeepSeek V4.1 Flash 1017 for raw capability and GLM-5.3-Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.3-Flash or DeepSeek V4.1 Flash 1017?
GLM-5.3-Flash is cheaper at $0.15 input / $0.50 output per million tokens (official Z.AI API price). DeepSeek V4.1 Flash 1017 costs $0.15 input / $0.60 output per million tokens (official DeepSeek API price). At a typical mix of three input tokens to one output token, that is $0.237 per million tokens for GLM-5.3-Flash versus $0.263 for DeepSeek V4.1 Flash 1017 (1.1× as much).
Which scores higher on benchmarks?
DeepSeek V4.1 Flash 1017 scores higher on the Capabilities Index (ECI): DeepSeek V4.1 Flash 1017 158.8 (#19 of 165) and GLM-5.3-Flash 153.2 (#48 of 165). Their confidence ranges do not overlap (156.7–162.2 vs 150.9–155.4), so the gap is a real one. On individual benchmarks: GPQA Diamond — DeepSeek V4.1 Flash 1017 93.2%, GLM-5.3-Flash 90.2%; FrontierMath Tiers 1–3 — DeepSeek V4.1 Flash 1017 71.2%, GLM-5.3-Flash 55.8%; OTIS Mock AIME 2024–2025 — DeepSeek V4.1 Flash 1017 99.4%, GLM-5.3-Flash 93.9%.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5.3-Flash and DeepSeek V4.1 Flash 1017 yet, so there is no like-for-like coding score. On overall capability, DeepSeek V4.1 Flash 1017 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
GLM-5.3-Flash and DeepSeek V4.1 Flash 1017 share the same 1,000,000-token context window. Maximum output per response: GLM-5.3-Flash up to 131,072, DeepSeek V4.1 Flash 1017 up to 384,000 tokens.
Which can read images, PDFs, audio or video?
GLM-5.3-Flash accepts text, images, PDFs and video; DeepSeek V4.1 Flash 1017 accepts text and images. GLM-5.3-Flash handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (MIT), so you can self-host them.
Which is newer?
DeepSeek V4.1 Flash 1017 is the newest, released Oct 17, 2026. GLM-5.3-Flash came out Aug 26, 2026. Knowledge cutoff: DeepSeek V4.1 Flash 1017 May 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 Nov 2, 2026.
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