DeepSeek V4.1 Flash vs Qwen3.8 Flash Next vs GLM-5.3-Flash
GLM-5.3-Flash comes out ahead, 79 to 72 and 70 on our weighted score, and it is the cheaper option too.
DeepSeek
DeepSeek V4.1 Flash
72/100- ECI155.0
- Price$0.15 / $0.60
- Context1M
Alibaba (Qwen)
Qwen3.8 Flash Next
70/100- ECI—
- Price$0.20 / $0.50
- Context262K
- Our pick
Z.ai (Zhipu)
GLM-5.3-Flash
79/100- ECI151.9
- Price$0.15 / $0.50
- Context1M
GLM-5.3-Flash is our pick
GLM-5.3-Flash is the better all-round choice, scoring 79/100 against DeepSeek V4.1 Flash (72) and Qwen3.8 Flash Next (70). It leads on price and inputs & features. 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-5.3-FlashGLM-5.3-Flash $0.237 · DeepSeek V4.1 Flash $0.263 · Qwen3.8 Flash Next $0.275 per 1M tokens (3:1 blend)
- Longest contextDeepSeek V4.1 Flash and GLM-5.3-FlashDeepSeek V4.1 Flash 1,000,000 · GLM-5.3-Flash 1,000,000 · Qwen3.8 Flash Next 262,144 tokens
- Widest inputsGLM-5.3-FlashDeepSeek V4.1 Flash: Text, Images · Qwen3.8 Flash Next: Text, Images, Video · GLM-5.3-Flash: Text, Images, PDFs, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek V4.1 Flash | Qwen3.8 Flash Next | GLM-5.3-Flash |
|---|---|---|---|---|
| Price | 50% | 77 | 76 | 79 |
| Inputs & features | 30% | 70 | 80 | 90 |
| Context window | 20% | 60 | 37 | 60 |
| Overall | 100% | 72/100 | 70/100 | 79/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 155.0 (best) | — | 151.9 |
| ECI rank | #29 of 148 (best) | — | #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 (best) | $0.20 | $0.15 (best) |
| Output | $0.60 | $0.50 (best) | $0.50 (best) |
| Cached input | $0.003 (best) | — | $0.03 |
| Blended (3:1) | $0.263 | $0.275 | $0.237 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official DeepSeek API | Median of 5 providers | Official Z.AI API |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 262,144 tokens | 1,000,000 tokens (best) |
| Max output | 384,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · high · max | Yes | Yeslow · high · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | OpenMIT | Openqwen-community-1.0 | Open |
| API model ID | deepseek-flash | — | glm-5.3-flash |
| API providers | 50 | 5 | 65 (best) |
| Released | Sep 10, 2026 | Aug 27, 2026 | Aug 26, 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.
DeepSeek V4.1 Flash$2.70
Qwen3.8 Flash Next$3.00
GLM-5.3-Flash$2.50
Which should you choose?
Which is better: DeepSeek V4.1 Flash, Qwen3.8 Flash Next or GLM-5.3-Flash?
GLM-5.3-Flash is the better all-round choice, scoring 79/100 against DeepSeek V4.1 Flash (72) and Qwen3.8 Flash Next (70). It leads on price and inputs & features. 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, DeepSeek V4.1 Flash, Qwen3.8 Flash Next or GLM-5.3-Flash?
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 costs $0.15 input / $0.60 output per million tokens (official DeepSeek API price); Qwen3.8 Flash Next costs $0.20 input / $0.50 output per million tokens (median across 5 API providers). 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 (1.1× as much) and $0.275 for Qwen3.8 Flash Next (1.2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DeepSeek V4.1 Flash has an ECI of 155.0, Qwen3.8 Flash Next has not been scored yet and GLM-5.3-Flash has an ECI of 151.9.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4.1 Flash, Qwen3.8 Flash Next and GLM-5.3-Flash yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
DeepSeek V4.1 Flash and GLM-5.3-Flash have the largest context windows (1,000,000 and 1,000,000 tokens), against 262,144 for Qwen3.8 Flash Next. Maximum output per response: DeepSeek V4.1 Flash up to 384,000, Qwen3.8 Flash Next up to 131,072, GLM-5.3-Flash up to 131,072 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4.1 Flash accepts text and images; Qwen3.8 Flash Next accepts text, images and video; GLM-5.3-Flash accepts text, images, PDFs and video. GLM-5.3-Flash handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (MIT and qwen-community-1.0), so you can self-host them.
Which is newer?
DeepSeek V4.1 Flash is the newest, released Sep 10, 2026. Qwen3.8 Flash Next came out Aug 27, 2026; GLM-5.3-Flash came out Aug 26, 2026. Knowledge cutoff: DeepSeek V4.1 Flash 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 Oct 4, 2026.