Phi-4-multimodal-instruct vs Trinity Mini vs Command R7B Arabic

Phi-4-multimodal-instruct is the better all-round choice, scoring 72/100 against Trinity Mini (65) and Command R7B Arabic (65). It leads 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.

Command R7B Arabic is cheaper at $0.037 input / $0.15 output per million tokens (official Cohere API price). 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 $0.066 per million tokens for Command R7B Arabic versus $0.071 for Trinity Mini (1.1× as much) and $0.08 for Phi-4-multimodal-instruct (1.2× as much).

There is no independent benchmark that covers all three models yet. Phi-4-multimodal-instruct has not been scored yet, Trinity Mini has not been scored yet and Command R7B Arabic has not been scored yet.

There are no published SWE-bench Verified results for Phi-4-multimodal-instruct, Trinity Mini and Command R7B Arabic 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.

Phi-4-multimodal-instruct and Trinity Mini have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Command R7B Arabic. Maximum output per response: Phi-4-multimodal-instruct up to 131,072, Trinity Mini up to 131,072, Command R7B Arabic up to 4,000 tokens.

Phi-4-multimodal-instruct accepts text, images and audio; Trinity Mini accepts text; Command R7B Arabic accepts text. Phi-4-multimodal-instruct handles the widest range of inputs.

Yes, all three publish their weights (MIT and OpenMDW-1.1), so you can self-host them.

Trinity Mini is the newest, released Dec 1, 2025. Command R7B Arabic came out Feb 27, 2025; Phi-4-multimodal-instruct came out Feb 26, 2025. Knowledge cutoff: Phi-4-multimodal-instruct Jun 2024, Command R7B Arabic Jun 1, 2024.

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.