QwQ Plus vs Llama 4 Maverick 17B Instruct

Llama 4 Maverick 17B Instruct is the better all-round choice, scoring 63/100 against QwQ Plus (52). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because QwQ Plus has no Capabilities Index score yet.

Llama 4 Maverick 17B Instruct is cheaper at $0.321 input / $0.91 output per million tokens (median across 6 API providers). QwQ Plus costs $0.80 input / $2.40 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.468 per million tokens for Llama 4 Maverick 17B Instruct versus $1.20 for QwQ Plus (2.6× as much).

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): Llama 4 Maverick 17B Instruct 67.0% and QwQ Plus 65.4%. On individual benchmarks: GPQA Diamond — Llama 4 Maverick 17B Instruct 67.0%, QwQ Plus 65.4%.

There are no published SWE-bench Verified results for QwQ Plus and Llama 4 Maverick 17B Instruct yet, so there is no like-for-like coding score. On overall capability, Llama 4 Maverick 17B Instruct leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Llama 4 Maverick 17B Instruct has the largest context window at 1,000,000 tokens, against 131,072 for QwQ Plus. Maximum output per response: QwQ Plus up to 8,192, Llama 4 Maverick 17B Instruct up to 16,384 tokens.

QwQ Plus accepts text; Llama 4 Maverick 17B Instruct accepts text and images. Llama 4 Maverick 17B Instruct handles the widest range of inputs.

Llama 4 Maverick 17B Instruct publishes its weights and can be self-hosted; QwQ Plus is proprietary.

Llama 4 Maverick 17B Instruct is the newest, released Apr 5, 2025. QwQ Plus came out Mar 5, 2025. Knowledge cutoff: QwQ Plus Apr 2024, Llama 4 Maverick 17B Instruct Aug 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 Oct 4, 2026.