DeepSeek V4 Flash Vision Exp vs GLM 5
At a Glance
| Compare | DeepSeek V4 Flash Vision ExpDeepSeek | GLM 5Z.ai |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.22DeepSeek ↗ · Sep 2, 2026 | $0.60Deepinfra ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $0.66DeepSeek ↗ · Sep 2, 2026 | $1.92Openrouter ↗ · Aug 28, 2026 |
| Context windowMaximum documented tokens | 1,049K | 203K |
| Model facts checked | Sep 2, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | DeepSeek-V4-Flash-Vision-Exp | GLM-5 |
|---|---|---|
| Developer | DeepSeek | Z.ai |
| Family | Deepseek V4 Flash Vision Exp | Glm 5 |
| Model | DeepSeek-V4-Flash-Vision-Exp | GLM-5 |
| Version | DeepSeek-V4-Flash-Vision-Exp | GLM-5 |
| Lifecycle | retired | active |
| Released | 2026-08-21 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,049K | 203K |
| Total parameters | 304.6B | 753.9B |
| Active parameters | Unknown | Unknown |
| License | mit | mit |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | DeepSeek (Standard), Deepinfra (Standard), Fireworks Ai (Standard) | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | chat, generation, reasoning, structured_outputs, tools | chat, generation, reasoning, tools |
DeepSeek V4 Flash Vision Exp Capabilities
GLM 5 Capabilities
Primary Evidence
Sources and Freshness
Questions
DeepSeek V4 Flash Vision Exp vs GLM 5 FAQs
Is DeepSeek V4 Flash Vision Exp or GLM 5 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4 Flash Vision Exp and GLM 5, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, DeepSeek V4 Flash Vision Exp or GLM 5?+
DeepSeek V4 Flash Vision Exp is $0.22 and GLM 5 is $0.60 per million tokens, so DeepSeek V4 Flash Vision Exp is cheaper on this metric. DeepSeek V4 Flash Vision Exp is $0.66 and GLM 5 is $1.92 per million tokens, so DeepSeek V4 Flash Vision Exp is cheaper on this metric.
Which has a larger context window, DeepSeek V4 Flash Vision Exp or GLM 5?+
DeepSeek V4 Flash Vision Exp has the larger sourced context window. DeepSeek V4 Flash Vision Exp supports 1,049K and GLM 5 supports 203K.
Which performs better in benchmarks, DeepSeek V4 Flash Vision Exp or GLM 5?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can DeepSeek V4 Flash Vision Exp or GLM 5 be self-hosted?+
Both models have the same recorded self-hosting status: supported. DeepSeek V4 Flash Vision Exp is open weight; GLM 5 is open weight.
Can DeepSeek V4 Flash Vision Exp and GLM 5 understand images?+
DeepSeek V4 Flash Vision Exp is documented with image input; GLM 5 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, DeepSeek V4 Flash Vision Exp or GLM 5?+
Neither has a larger sourced maximum output. DeepSeek V4 Flash Vision Exp is 393K and GLM 5 is —.
Do DeepSeek V4 Flash Vision Exp and GLM 5 support reasoning and tool use?+
DeepSeek V4 Flash Vision Exp: reasoning, tool calling, and image input. GLM 5: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek V4 Flash Vision Exp or GLM 5?+
DeepSeek V4 Flash Vision Exp has 3 sourced provider routes; GLM 5 has 4, so GLM 5 has broader tracked availability.
Which offers better value, DeepSeek V4 Flash Vision Exp or GLM 5?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.