Viv Fast vs Qwen3.8 Max vs MiMo-V2.6-Flash
MiMo-V2.6-Flash comes out ahead, 79 to 75 and 53 on our weighted score, and it is the cheaper option too.
VivgridViv Fast
75/100- ECI—
- Price$0.13 / $0.40
- Context1M
Alibaba (Qwen)Qwen3.8 Max
53/100- ECI156.6
- Price$2.00 / $6.00
- Context1M
- Our pick
XiaomiMiMo-V2.6-Flash
79/100- ECI—
- Price$0.14 / $0.28
- Context1.05M
MiMo-V2.6-Flash is our pick
MiMo-V2.6-Flash is the better all-round choice, scoring 79/100 against Viv Fast (75) and Qwen3.8 Max (53). It leads on price. Qwen3.8 Max 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 priceMiMo-V2.6-FlashMiMo-V2.6-Flash $0.175 · Viv Fast $0.198 · Qwen3.8 Max $3.00 per 1M tokens (3:1 blend)
- Longest contextMiMo-V2.6-FlashMiMo-V2.6-Flash 1,048,576 · Viv Fast 1,000,000 · Qwen3.8 Max 1,000,000 tokens
- Widest inputsQwen3.8 Max and MiMo-V2.6-FlashViv Fast: Text, Images · Qwen3.8 Max: Text, Images, PDFs, Video · MiMo-V2.6-Flash: Text, Images, Audio, Video
- Self-hostingMiMo-V2.6-FlashPublishes downloadable weights
| Measure | Weight | Viv Fast | Qwen3.8 Max | MiMo-V2.6-Flash |
|---|---|---|---|---|
| Price | 50% | 83 | 27 | 86 |
| Inputs & features | 30% | 70 | 90 | 80 |
| Context window | 20% | 60 | 60 | 61 |
| Overall | 100% | 75/100 | 53/100 | 79/100 |
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 | Viv FastVivgrid | Qwen3.8 MaxAlibaba (Qwen) | MiMo-V2.6-FlashXiaomi |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 156.6 | — |
| ECI rank | — | #20 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 92.7% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 74.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 99.4% | — |
| SimpleQA VerifiedShort factual questions | — | 45.8% | — |
| Price per million tokens | |||
| Input | $0.13 (best) | $2.00 | $0.14 |
| Output | $0.40 | $6.00 | $0.28 (best) |
| Cached input | $0.05 | $0.25 | $0.0028 (best) |
| Blended (3:1) | $0.198 | $3.00 | $0.175 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Vivgrid API | Official Alibaba API | Official Xiaomi API |
| Limits | |||
| Context window | 1,000,000 tokens | 1,000,000 tokens | 1,048,576 tokens (best) |
| Max output | 256,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | Yes |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · high · max | Yeslow · medium · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | viv-fast | qwen3.8-max | mimo-v2.6-flash |
| API providers | 1 | 25 (best) | 18 |
| Released | Sep 21, 2026 | Aug 3, 2026 | Sep 22, 2026 |
| Knowledge cutoff | Sep 2026 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Viv Fast$2.10
- Qwen3.8 Max$32.00
- MiMo-V2.6-Flash$1.96
Which should you choose?
Which is better: Viv Fast, Qwen3.8 Max or MiMo-V2.6-Flash?
MiMo-V2.6-Flash is the better all-round choice, scoring 79/100 against Viv Fast (75) and Qwen3.8 Max (53). It leads on price. Qwen3.8 Max 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, Viv Fast, Qwen3.8 Max or MiMo-V2.6-Flash?
MiMo-V2.6-Flash is cheaper at $0.14 input / $0.28 output per million tokens (official Xiaomi API price). Viv Fast costs $0.13 input / $0.40 output per million tokens (official Vivgrid API price); Qwen3.8 Max costs $2.00 input / $6.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for MiMo-V2.6-Flash versus $0.198 for Viv Fast (1.1× as much) and $3.00 for Qwen3.8 Max (17× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Viv Fast has not been scored yet, Qwen3.8 Max has an ECI of 156.6 and MiMo-V2.6-Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Viv Fast, Qwen3.8 Max and MiMo-V2.6-Flash 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?
MiMo-V2.6-Flash has the largest context window at 1,048,576 tokens, against 1,000,000 for Viv Fast and 1,000,000 for Qwen3.8 Max. Maximum output per response: Viv Fast up to 256,000, Qwen3.8 Max up to 131,072, MiMo-V2.6-Flash up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Viv Fast accepts text and images; Qwen3.8 Max accepts text, images, PDFs and video; MiMo-V2.6-Flash accepts text, images, audio and video. Qwen3.8 Max handles the widest range of inputs.
Are any of these open source?
MiMo-V2.6-Flash publishes its weights and can be self-hosted; Viv Fast and Qwen3.8 Max is proprietary.
Which is newer?
MiMo-V2.6-Flash is the newest, released Sep 22, 2026. Viv Fast came out Sep 21, 2026; Qwen3.8 Max came out Aug 3, 2026. Knowledge cutoff: Viv Fast Sep 2026.
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 Oct 4, 2026.
