Grok 4.20 (Non-Reasoning) vs Macaron V1 Venti vs MiMo-V2-Pro
Grok 4.20 (Non-Reasoning) comes out ahead, 52 to 44 and 42 on our weighted score, though Macaron V1 Venti is 21% cheaper per token.
- Our pick
xAIGrok 4.20 (Non-Reasoning)
52/100- ECI—
- Price$1.25 / $2.50
- Context1M
Mindlab
Macaron V1 Venti
44/100- ECI—
- Price$0.825 / $2.48
- Context1.05M
XiaomiMiMo-V2-Pro
42/100- ECI—
- Price$1.00 / $3.00
- Context1.05M
Grok 4.20 (Non-Reasoning) is our pick
Grok 4.20 (Non-Reasoning) is the better all-round choice, scoring 52/100 against Macaron V1 Venti (44) and MiMo-V2-Pro (42). It leads on inputs & features. Macaron V1 Venti wins on price. 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 priceMacaron V1 VentiMacaron V1 Venti $1.24 · MiMo-V2-Pro $1.50 · Grok 4.20 (Non-Reasoning) $1.56 per 1M tokens (3:1 blend)
- Longest contextMacaron V1 Venti and MiMo-V2-ProMacaron V1 Venti 1,048,576 · MiMo-V2-Pro 1,048,576 · Grok 4.20 (Non-Reasoning) 1,000,000 tokens
- Widest inputsGrok 4.20 (Non-Reasoning)Grok 4.20 (Non-Reasoning): Text, Images, PDFs · Macaron V1 Venti: Text · MiMo-V2-Pro: Text
- Self-hostingMacaron V1 VentiPublishes downloadable weights (MIT)
| Measure | Weight | Grok 4.20 (Non-Reasoning) | Macaron V1 Venti | MiMo-V2-Pro |
|---|---|---|---|---|
| Price | 50% | 39 | 44 | 40 |
| Inputs & features | 30% | 70 | 35 | 35 |
| Context window | 20% | 60 | 61 | 61 |
| Overall | 100% | 52/100 | 44/100 | 42/100 |
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 | Grok 4.20 (Non-Reasoning)xAI | Macaron V1 VentiMindlab | MiMo-V2-ProXiaomi |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.25 | $0.825 (best) | $1.00 |
| Output | $2.50 | $2.48 (best) | $3.00 |
| Cached input | $0.20 | — | — |
| Blended (3:1) | $1.56 | $1.24 (best) | $1.50 |
| Long-context rate | Over 200K: $2.50 / $5.00 | Same rate | Same rate |
| Price source | Official xAI API | Median of 1 providers | Median of 1 providers |
| Limits | |||
| Context window | 1,000,000 tokens | 1,048,576 tokens (best) | 1,048,576 tokens (best) |
| Max output | 30,000 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | OpenMIT | Proprietary |
| API model ID | grok-4.20-0309-non-reasoning | — | — |
| API providers | 13 (best) | 1 | 2 |
| Released | Mar 9, 2026 | Jul 21, 2026 | Mar 18, 2026 |
| Knowledge cutoff | — | — | Dec 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Grok 4.20 (Non-Reasoning)$17.50
- Macaron V1 Venti$13.20
- MiMo-V2-Pro$16.00
Which should you choose?
Which is better: Grok 4.20 (Non-Reasoning), Macaron V1 Venti or MiMo-V2-Pro?
Grok 4.20 (Non-Reasoning) is the better all-round choice, scoring 52/100 against Macaron V1 Venti (44) and MiMo-V2-Pro (42). It leads on inputs & features. Macaron V1 Venti wins on price. 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, Grok 4.20 (Non-Reasoning), Macaron V1 Venti or MiMo-V2-Pro?
Macaron V1 Venti is cheaper at $0.825 input / $2.48 output per million tokens (median across 1 API provider). MiMo-V2-Pro costs $1.00 input / $3.00 output per million tokens (median across 1 API provider); Grok 4.20 (Non-Reasoning) costs $1.25 input / $2.50 output per million tokens (official xAI API price). At a typical mix of three input tokens to one output token, that is $1.24 per million tokens for Macaron V1 Venti versus $1.50 for MiMo-V2-Pro (1.2× as much) and $1.56 for Grok 4.20 (Non-Reasoning) (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Grok 4.20 (Non-Reasoning) has not been scored yet, Macaron V1 Venti has not been scored yet and MiMo-V2-Pro has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Grok 4.20 (Non-Reasoning), Macaron V1 Venti and MiMo-V2-Pro 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?
Macaron V1 Venti and MiMo-V2-Pro have the largest context windows (1,048,576 and 1,048,576 tokens), against 1,000,000 for Grok 4.20 (Non-Reasoning). Maximum output per response: Grok 4.20 (Non-Reasoning) up to 30,000, Macaron V1 Venti up to 131,072, MiMo-V2-Pro up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Grok 4.20 (Non-Reasoning) accepts text, images and PDFs; Macaron V1 Venti accepts text; MiMo-V2-Pro accepts text. Grok 4.20 (Non-Reasoning) handles the widest range of inputs.
Are any of these open source?
Macaron V1 Venti publishes its weights (MIT) and can be self-hosted; Grok 4.20 (Non-Reasoning) and MiMo-V2-Pro is proprietary.
Which is newer?
Macaron V1 Venti is the newest, released Jul 21, 2026. MiMo-V2-Pro came out Mar 18, 2026; Grok 4.20 (Non-Reasoning) came out Mar 9, 2026. Knowledge cutoff: MiMo-V2-Pro Dec 2024.
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.
