Trinity Mini vs Phi-4-multimodal-instruct vs Qwen3 VL Flash (Alibaba Cloud)
Too close to call on our weighted score (Qwen3 VL Flash (Alibaba Cloud) 72, Phi-4-multimodal-instruct 72, Trinity Mini 65). The right pick depends on what you value most.
Arcee AI
Trinity Mini
65/100- ECI—
- Price$0.045 / $0.15
- Context131K
Microsoft
Phi-4-multimodal-instruct
72/100- ECI—
- Price$0.07 / $0.11
- Context131K
Alibaba (Qwen)
Qwen3 VL Flash (Alibaba Cloud)
72/100- ECI—
- Price$0.022 / $0.215
- Context262K
Too close to call
It is close. Our weighted score puts them within a point (Qwen3 VL Flash (Alibaba Cloud) 72/100, Phi-4-multimodal-instruct 72/100, Trinity Mini 65/100), so choose by what matters most for your work: Qwen3 VL Flash (Alibaba Cloud) on price and Qwen3 VL Flash (Alibaba Cloud) for long inputs. 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 priceQwen3 VL Flash (Alibaba Cloud)Qwen3 VL Flash (Alibaba Cloud) $0.07 · Trinity Mini $0.071 · Phi-4-multimodal-instruct $0.08 per 1M tokens (3:1 blend)
- Longest contextQwen3 VL Flash (Alibaba Cloud)Qwen3 VL Flash (Alibaba Cloud) 262,144 · Trinity Mini 131,072 · Phi-4-multimodal-instruct 131,072 tokens
- Widest inputsPhi-4-multimodal-instructTrinity Mini: Text · Phi-4-multimodal-instruct: Text, Images, Audio · Qwen3 VL Flash (Alibaba Cloud): Text, Images
- Self-hostingTrinity Mini and Phi-4-multimodal-instructPublishes downloadable weights (OpenMDW-1.1 and MIT)
| Measure | Weight | Trinity Mini | Phi-4-multimodal-instruct | Qwen3 VL Flash (Alibaba Cloud) |
|---|---|---|---|---|
| Price | 50% | 100 | 98 | 100 |
| Inputs & features | 30% | 35 | 60 | 50 |
| Context window | 20% | 25 | 25 | 37 |
| Overall | 100% | 65/100 | 72/100 | 72/100 |
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 | $0.045 | $0.07 | $0.022 (best) |
| Output | $0.15 | $0.11 (best) | $0.215 |
| Cached input | — | — | — |
| Blended (3:1) | $0.071 | $0.08 | $0.07 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 1 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens | 131,072 tokens | 262,144 tokens (best) |
| Max output | 131,072 tokens (best) | 131,072 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenOpenMDW-1.1 | OpenMIT | Proprietary |
| API model ID | — | — | — |
| API providers | 1 | 1 | 1 |
| Released | Dec 1, 2025 | Feb 26, 2025 | Oct 15, 2025 |
| Knowledge cutoff | — | Jun 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Trinity Mini$0.75
Phi-4-multimodal-instruct$0.92
Qwen3 VL Flash (Alibaba Cloud)$0.65
Which should you choose?
Which is better: Trinity Mini, Phi-4-multimodal-instruct or Qwen3 VL Flash (Alibaba Cloud)?
It is close. Our weighted score puts them within a point (Qwen3 VL Flash (Alibaba Cloud) 72/100, Phi-4-multimodal-instruct 72/100, Trinity Mini 65/100), so choose by what matters most for your work: Qwen3 VL Flash (Alibaba Cloud) on price and Qwen3 VL Flash (Alibaba Cloud) for long inputs. 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, Trinity Mini, Phi-4-multimodal-instruct or Qwen3 VL Flash (Alibaba Cloud)?
Qwen3 VL Flash (Alibaba Cloud) is cheaper at $0.022 input / $0.215 output per million tokens (median across 1 API provider). Trinity Mini costs $0.045 input / $0.15 output per million tokens (median across 1 API provider); Phi-4-multimodal-instruct costs $0.07 input / $0.11 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.07 per million tokens for Qwen3 VL Flash (Alibaba Cloud) versus $0.071 for Trinity Mini (1× as much) and $0.08 for Phi-4-multimodal-instruct (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Trinity Mini has not been scored yet, Phi-4-multimodal-instruct has not been scored yet and Qwen3 VL Flash (Alibaba Cloud) has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Trinity Mini, Phi-4-multimodal-instruct and Qwen3 VL Flash (Alibaba Cloud) 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?
Qwen3 VL Flash (Alibaba Cloud) has the largest context window at 262,144 tokens, against 131,072 for Trinity Mini and 131,072 for Phi-4-multimodal-instruct. Maximum output per response: Trinity Mini up to 131,072, Phi-4-multimodal-instruct up to 131,072, Qwen3 VL Flash (Alibaba Cloud) up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Trinity Mini accepts text; Phi-4-multimodal-instruct accepts text, images and audio; Qwen3 VL Flash (Alibaba Cloud) accepts text and images. Phi-4-multimodal-instruct handles the widest range of inputs.
Are any of these open source?
Trinity Mini and Phi-4-multimodal-instruct publishes its weights (OpenMDW-1.1 and MIT) and can be self-hosted; Qwen3 VL Flash (Alibaba Cloud) is proprietary.
Which is newer?
Trinity Mini is the newest, released Dec 1, 2025. Qwen3 VL Flash (Alibaba Cloud) came out Oct 15, 2025; Phi-4-multimodal-instruct came out Feb 26, 2025. Knowledge cutoff: Phi-4-multimodal-instruct Jun 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.