GLM-4.6V-Flash vs Grok 4 Fast Non Reasoning vs Qwen3 Omni 30B A3B Thinking
Grok 4 Fast Non Reasoning comes out ahead, 72 to 63 and 59 on our weighted score, though GLM-4.6V-Flash is 5% cheaper per token.
Z.ai (Zhipu)
GLM-4.6V-Flash
63/100- ECI—
- Price$0.161 / $0.559
- Context128K
- Our pick
xAI
Grok 4 Fast Non Reasoning
72/100- ECI—
- Price$0.20 / $0.50
- Context2M
Alibaba (Qwen)
Qwen3 Omni 30B A3B Thinking
59/100- ECI—
- Price$0.25 / $0.97
- Context66K
Grok 4 Fast Non Reasoning is our pick
Grok 4 Fast Non Reasoning is the better all-round choice, scoring 72/100 against GLM-4.6V-Flash (63) and Qwen3 Omni 30B A3B Thinking (59). It leads on context window. Qwen3 Omni 30B A3B Thinking wins on 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-4.6V-FlashGLM-4.6V-Flash $0.261 · Grok 4 Fast Non Reasoning $0.275 · Qwen3 Omni 30B A3B Thinking $0.43 per 1M tokens (3:1 blend)
- Longest contextGrok 4 Fast Non ReasoningGrok 4 Fast Non Reasoning 2,000,000 · GLM-4.6V-Flash 128,000 · Qwen3 Omni 30B A3B Thinking 65,536 tokens
- Widest inputsGrok 4 Fast Non Reasoning and Qwen3 Omni 30B A3B ThinkingGLM-4.6V-Flash: Text, Images, Video · Grok 4 Fast Non Reasoning: Text, Images, Audio, Video · Qwen3 Omni 30B A3B Thinking: Text, Images, Audio, Video
- Self-hostingGLM-4.6V-Flash and Qwen3 Omni 30B A3B ThinkingPublishes downloadable weights (Apache-2.0)
| Measure | Weight | GLM-4.6V-Flash | Grok 4 Fast Non Reasoning | Qwen3 Omni 30B A3B Thinking |
|---|---|---|---|---|
| Price | 50% | 74 | 73 | 64 |
| Inputs & features | 30% | 70 | 70 | 80 |
| Context window | 20% | 24 | 72 | 12 |
| Overall | 100% | 63/100 | 72/100 | 59/100 |
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) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.161 (best) | $0.20 | $0.25 |
| Output | $0.559 | $0.50 (best) | $0.97 |
| Cached input | — | — | — |
| Blended (3:1) | $0.261 (best) | $0.275 | $0.43 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 7 providers | Median of 1 providers |
| Limits | |||
| Context window | 128,000 tokens | 2,000,000 tokens (best) | 65,536 tokens |
| Max output | 32,768 tokens | 2,000,000 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | Yes | Yes |
| Video | Yes | Yes | Yes |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | OpenApache-2.0 |
| API model ID | glm-4.6v-flash | — | — |
| API providers | 6 | 8 (best) | 1 |
| Released | Dec 8, 2025 | Dec 18, 2025 | Sep 22, 2025 |
| Knowledge cutoff | — | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
GLM-4.6V-Flash$2.73
Grok 4 Fast Non Reasoning$3.00
Qwen3 Omni 30B A3B Thinking$4.44
Which should you choose?
Which is better: GLM-4.6V-Flash, Grok 4 Fast Non Reasoning or Qwen3 Omni 30B A3B Thinking?
Grok 4 Fast Non Reasoning is the better all-round choice, scoring 72/100 against GLM-4.6V-Flash (63) and Qwen3 Omni 30B A3B Thinking (59). It leads on context window. Qwen3 Omni 30B A3B Thinking wins on 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, GLM-4.6V-Flash, Grok 4 Fast Non Reasoning or Qwen3 Omni 30B A3B Thinking?
GLM-4.6V-Flash is cheaper at $0.161 input / $0.559 output per million tokens (median across 2 API providers; free on Z.AI). Grok 4 Fast Non Reasoning costs $0.20 input / $0.50 output per million tokens (median across 7 API providers); Qwen3 Omni 30B A3B Thinking costs $0.25 input / $0.97 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.261 per million tokens for GLM-4.6V-Flash versus $0.275 for Grok 4 Fast Non Reasoning (1.1× as much) and $0.43 for Qwen3 Omni 30B A3B Thinking (1.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.6V-Flash has not been scored yet, Grok 4 Fast Non Reasoning has not been scored yet and Qwen3 Omni 30B A3B Thinking has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.6V-Flash, Grok 4 Fast Non Reasoning and Qwen3 Omni 30B A3B Thinking 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?
Grok 4 Fast Non Reasoning has the largest context window at 2,000,000 tokens, against 128,000 for GLM-4.6V-Flash and 65,536 for Qwen3 Omni 30B A3B Thinking. Maximum output per response: GLM-4.6V-Flash up to 32,768, Grok 4 Fast Non Reasoning up to 2,000,000, Qwen3 Omni 30B A3B Thinking up to 16,384 tokens.
Which can read images, PDFs, audio or video?
GLM-4.6V-Flash accepts text, images and video; Grok 4 Fast Non Reasoning accepts text, images, audio and video; Qwen3 Omni 30B A3B Thinking accepts text, images, audio and video. Grok 4 Fast Non Reasoning handles the widest range of inputs.
Are any of these open source?
GLM-4.6V-Flash and Qwen3 Omni 30B A3B Thinking publishes its weights (Apache-2.0) and can be self-hosted; Grok 4 Fast Non Reasoning is proprietary.
Which is newer?
Grok 4 Fast Non Reasoning is the newest, released Dec 18, 2025. GLM-4.6V-Flash came out Dec 8, 2025; Qwen3 Omni 30B A3B Thinking came out Sep 22, 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.