AI model comparison
DeepSeek V4.1 Flash vs GLM 5 Turbo
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture.
- Input / 1M
- $0.15
- Output / 1M
- $0.60
- Context
- 1.05M
GLM-5 Turbo is a new model from Z.ai designed for fast inference and strong performance in agent-driven environments such as OpenClaw scenarios.
- Input / 1M
- $1.20
- Output / 1M
- $4
- Context
- 203K
Comparing image generators? Compare image models
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
DeepSeek V4.1 Flash
7.3x cheaper for a typical chat
Higher intelligence score
GLM 5 Turbo
26.6 vs 24.7 on Artificial Analysis
Larger context window
DeepSeek V4.1 Flash
1.05M vs 203K tokens
Newer release
DeepSeek V4.1 Flash
Released September 10, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
DeepSeek V4.1 Flash vs GLM 5 Turbo API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.15 | $1.20 |
| Output tokensPer 1M tokens | $0.60 | $4 |
| Cached input (read)Per 1M tokens | $0.00 | $0.24 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 1.05M tokens | 203K tokens |
| Max output | 393K tokens | 131K tokens |
| Input types | Image, Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Max, High, Low, None | Not available |
| Default reasoning effort | High | Not available |
| Release date | September 10, 2026 | March 15, 2026 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Not supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Not supported |
| Deterministic seed | Supported | Not supported |
| Verbosity control | Not supported | Not supported |
Our take
DeepSeek V4.1 Flash is 7.3x cheaper for a typical chat. GLM 5 Turbo scores higher on the Artificial Analysis Intelligence Index (26.6 vs 24.7). DeepSeek V4.1 Flash has the larger context window (1.05M vs 203K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is DeepSeek V4.1 Flash or GLM 5 Turbo cheaper?
DeepSeek V4.1 Flash is cheaper for a typical chat (2K input tokens and 500 output tokens). DeepSeek V4.1 Flash costs $0.15 per 1M input tokens and $0.60 per 1M output tokens, while GLM 5 Turbo costs $1.20 per 1M input tokens and $4 per 1M output tokens.
Which has a bigger context window, DeepSeek V4.1 Flash or GLM 5 Turbo?
DeepSeek V4.1 Flash supports up to 1.05M tokens of context, compared with 203K for GLM 5 Turbo.
Is DeepSeek V4.1 Flash smarter than GLM 5 Turbo?
On the Artificial Analysis Intelligence Index, DeepSeek V4.1 Flash scores 24.7 and GLM 5 Turbo scores 26.6, putting GLM 5 Turbo ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use DeepSeek V4.1 Flash and GLM 5 Turbo at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see DeepSeek V4.1 Flash and GLM 5 Turbo answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to DeepSeek V4.1 Flash and GLM 5 Turbo at the same time. Compare the answers side by side and keep the best one.