DeepSeek V4.1 Flash vs Qwen3.8 27B vs GLM-5.3-Flash
Too close to call on our weighted score (GLM-5.3-Flash 80, DeepSeek V4.1 Flash 78, Qwen3.8 27B 67). The right pick depends on what you value most.
DeepSeek
DeepSeek V4.1 Flash
78/100- ECI155.0
- Price$0.15 / $0.60
- Context1M
Alibaba (Qwen)
Qwen3.8 27B
67/100- ECI149.4
- Price$0.40 / $2.50
- Context262K
Z.ai (Zhipu)
GLM-5.3-Flash
80/100- ECI151.9
- Price$0.15 / $0.50
- Context1M
Too close to call
It is close. Our weighted score puts them within 2 points (GLM-5.3-Flash 80/100, DeepSeek V4.1 Flash 78/100, Qwen3.8 27B 67/100), so choose by what matters most for your work: DeepSeek V4.1 Flash 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 FlashCapabilities Index (ECI): DeepSeek V4.1 Flash 155.0 · GLM-5.3-Flash 151.9 · Qwen3.8 27B 149.4
- Lowest priceGLM-5.3-FlashGLM-5.3-Flash $0.237 · DeepSeek V4.1 Flash $0.263 · Qwen3.8 27B $0.925 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 27B 262,144 tokens
- Widest inputsGLM-5.3-FlashDeepSeek V4.1 Flash: Text, Images · Qwen3.8 27B: 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 27B | GLM-5.3-Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 84 | 77 | 81 |
| Price | 25% | 77 | 51 | 79 |
| Inputs & features | 15% | 70 | 80 | 90 |
| Context window | 10% | 60 | 37 | 60 |
| Overall | 100% | 78/100 | 67/100 | 80/100 |
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) | 149.4 | 151.9 |
| ECI rank | #29 of 148 (best) | #53 of 148 | #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) | $0.40 | $0.15 (best) |
| Output | $0.60 | $2.50 | $0.50 (best) |
| Cached input | $0.003 (best) | — | $0.03 |
| Blended (3:1) | $0.263 | $0.925 | $0.237 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official DeepSeek API | Median of 39 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) | 32,768 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 | Open | Open |
| API model ID | deepseek-flash | — | glm-5.3-flash |
| API providers | 50 | 41 | 65 (best) |
| Released | Sep 10, 2026 | Aug 14, 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 27B$9.00
GLM-5.3-Flash$2.50
Which should you choose?
Which is better: DeepSeek V4.1 Flash, Qwen3.8 27B or GLM-5.3-Flash?
It is close. Our weighted score puts them within 2 points (GLM-5.3-Flash 80/100, DeepSeek V4.1 Flash 78/100, Qwen3.8 27B 67/100), so choose by what matters most for your work: DeepSeek V4.1 Flash 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, DeepSeek V4.1 Flash, Qwen3.8 27B 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 27B costs $0.40 input / $2.50 output per million tokens (median across 39 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 $0.925 for Qwen3.8 27B (3.9× as much).
Which scores higher on benchmarks?
DeepSeek V4.1 Flash scores higher on the Capabilities Index (ECI): DeepSeek V4.1 Flash 155.0 (#29 of 148), GLM-5.3-Flash 151.9 (#42 of 148) and Qwen3.8 27B 149.4 (#53 of 148). The confidence ranges of the top two overlap (148.8–157.6 vs 149.4–154.3), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4.1 Flash, Qwen3.8 27B and GLM-5.3-Flash yet, so there is no like-for-like coding score. On overall capability, DeepSeek V4.1 Flash leads, which tends to carry over to coding, but test on your own codebase. 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 27B. Maximum output per response: DeepSeek V4.1 Flash up to 384,000, Qwen3.8 27B up to 32,768, 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 27B 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), so you can self-host them.
Which is newer?
DeepSeek V4.1 Flash is the newest, released Sep 10, 2026. GLM-5.3-Flash came out Aug 26, 2026; Qwen3.8 27B came out Aug 14, 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.