Qwen3 VL 235B A22B Instruct vs GLM-4.6V-Flash vs Grok Code Fast 1
GLM-4.6V-Flash comes out ahead, 63 to 49 and 48 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3 VL 235B A22B Instruct
49/100- ECI—
- Price$0.30 / $1.55
- Context131K
- Our pick
Z.ai (Zhipu)GLM-4.6V-Flash
63/100- ECI—
- Price$0.161 / $0.559
- Context128K
xAIGrok Code Fast 1
48/100- ECI—
- Price$0.20 / $1.50
- Context256K
GLM-4.6V-Flash is our pick
GLM-4.6V-Flash is the better all-round choice, scoring 63/100 against Qwen3 VL 235B A22B Instruct (49) and Grok Code Fast 1 (48). It leads on price and inputs & features. Grok Code Fast 1 wins on context window. 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 Code Fast 1 $0.525 · Qwen3 VL 235B A22B Instruct $0.613 per 1M tokens (3:1 blend)
- Longest contextGrok Code Fast 1Grok Code Fast 1 256,000 · Qwen3 VL 235B A22B Instruct 131,072 · GLM-4.6V-Flash 128,000 tokens
- Widest inputsGLM-4.6V-FlashQwen3 VL 235B A22B Instruct: Text, Images · GLM-4.6V-Flash: Text, Images, Video · Grok Code Fast 1: Text
- Self-hostingQwen3 VL 235B A22B Instruct and GLM-4.6V-FlashPublishes downloadable weights
| Measure | Weight | Qwen3 VL 235B A22B Instruct | GLM-4.6V-Flash | Grok Code Fast 1 |
|---|---|---|---|---|
| Price | 50% | 57 | 74 | 60 |
| Inputs & features | 30% | 50 | 70 | 35 |
| Context window | 20% | 25 | 24 | 36 |
| Overall | 100% | 49/100 | 63/100 | 48/100 |
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 | Qwen3 VL 235B A22B InstructAlibaba (Qwen) | GLM-4.6V-FlashZ.ai (Zhipu) | Grok Code Fast 1xAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | $0.161 (best) | $0.20 |
| Output | $1.55 | $0.559 (best) | $1.50 |
| Cached input | — | — | — |
| Blended (3:1) | $0.613 | $0.261 (best) | $0.525 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 16 providers | Median of 2 providers | Median of 5 providers |
| Limits | |||
| Context window | 131,072 tokens | 128,000 tokens | 256,000 tokens (best) |
| Max output | 32,768 tokens (best) | 32,768 tokens (best) | 10,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | Yes | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | glm-4.6v-flash | — |
| API providers | 16 (best) | 6 | 7 |
| Released | Sep 23, 2025 | Dec 8, 2025 | Sep 2, 2025 |
| Knowledge cutoff | Mar 31, 2025 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Qwen3 VL 235B A22B Instruct$6.10
- GLM-4.6V-Flash$2.73
- Grok Code Fast 1$5.00
Which should you choose?
Which is better: Qwen3 VL 235B A22B Instruct, GLM-4.6V-Flash or Grok Code Fast 1?
GLM-4.6V-Flash is the better all-round choice, scoring 63/100 against Qwen3 VL 235B A22B Instruct (49) and Grok Code Fast 1 (48). It leads on price and inputs & features. Grok Code Fast 1 wins on context window. 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, Qwen3 VL 235B A22B Instruct, GLM-4.6V-Flash or Grok Code Fast 1?
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 Code Fast 1 costs $0.20 input / $1.50 output per million tokens (median across 5 API providers); Qwen3 VL 235B A22B Instruct costs $0.30 input / $1.55 output per million tokens (median across 16 API providers). 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 $0.525 for Grok Code Fast 1 (2× as much) and $0.613 for Qwen3 VL 235B A22B Instruct (2.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3 VL 235B A22B Instruct has not been scored yet, GLM-4.6V-Flash has not been scored yet and Grok Code Fast 1 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 VL 235B A22B Instruct, GLM-4.6V-Flash and Grok Code Fast 1 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 Code Fast 1 has the largest context window at 256,000 tokens, against 131,072 for Qwen3 VL 235B A22B Instruct and 128,000 for GLM-4.6V-Flash. Maximum output per response: Qwen3 VL 235B A22B Instruct up to 32,768, GLM-4.6V-Flash up to 32,768, Grok Code Fast 1 up to 10,000 tokens.
Which can read images, PDFs, audio or video?
Qwen3 VL 235B A22B Instruct accepts text and images; GLM-4.6V-Flash accepts text, images and video; Grok Code Fast 1 accepts text. GLM-4.6V-Flash handles the widest range of inputs.
Are any of these open source?
Qwen3 VL 235B A22B Instruct and GLM-4.6V-Flash publishes its weights and can be self-hosted; Grok Code Fast 1 is proprietary.
Which is newer?
GLM-4.6V-Flash is the newest, released Dec 8, 2025. Qwen3 VL 235B A22B Instruct came out Sep 23, 2025; Grok Code Fast 1 came out Sep 2, 2025. Knowledge cutoff: Qwen3 VL 235B A22B Instruct Mar 31, 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.
