Llama 4 Maverick 17B Instruct vs QwQ Plus vs DeepSeek-V3
Llama 4 Maverick 17B Instruct comes out ahead, 63 to 52 and 50 on our weighted score, and it is the cheaper option too.
- Our pick
Meta
Llama 4 Maverick 17B Instruct
63/100- ECI132.2
- Price$0.321 / $0.91
- Context1M
Alibaba (Qwen)
QwQ Plus
52/100- ECI—
- Price$0.80 / $2.40
- Context131K
DeepSeek
DeepSeek-V3
50/100- ECI132.3
- Price$0.32 / $1.10
- Context131K
Llama 4 Maverick 17B Instruct is our pick
Llama 4 Maverick 17B Instruct is the better all-round choice, scoring 63/100 against QwQ Plus (52) and DeepSeek-V3 (50). 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.
- CapabilityLlama 4 Maverick 17B InstructShared benchmarks: Llama 4 Maverick 17B Instruct 67.0% · QwQ Plus 65.4% · DeepSeek-V3 56.5%
- Lowest priceLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct $0.468 · DeepSeek-V3 $0.515 · QwQ Plus $1.20 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct 1,000,000 · QwQ Plus 131,072 · DeepSeek-V3 131,072 tokens
- Widest inputsLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct: Text, Images · QwQ Plus: Text · DeepSeek-V3: Text
- Self-hostingLlama 4 Maverick 17B Instruct and DeepSeek-V3Publishes downloadable weights (DeepSeek Model License)
| Measure | Weight | Llama 4 Maverick 17B Instruct | QwQ Plus | DeepSeek-V3 |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 67 | 65 | 57 |
| Price | 25% | 66 | 46 | 64 |
| Inputs & features | 15% | 50 | 35 | 25 |
| Context window | 10% | 60 | 24 | 24 |
| Overall | 100% | 63/100 | 52/100 | 50/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 132.2 | — | 132.3 (best) |
| ECI rank | #122 of 148 | — | #121 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 67.0% (best) | 65.4% | 56.5% |
| OTIS Mock AIME 2024–2025Competition mathematics | 20.6% (best) | — | 15.8% |
| Price per million tokens | |||
| Input | $0.321 | $0.80 | $0.32 (best) |
| Output | $0.91 (best) | $2.40 | $1.10 |
| Cached input | — | — | — |
| Blended (3:1) | $0.468 (best) | $1.20 | $0.515 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 6 providers | Official Alibaba API | Median of 5 providers |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Max output | 16,384 tokens (best) | 8,192 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | OpenDeepSeek Model License |
| API model ID | — | qwq-plus | — |
| API providers | 6 (best) | 2 | 5 |
| Released | Apr 5, 2025 | Mar 5, 2025 | Dec 26, 2024 |
| Knowledge cutoff | Aug 2024 | Apr 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Llama 4 Maverick 17B Instruct$5.03
QwQ Plus$12.80
DeepSeek-V3$5.40
Which should you choose?
Which is better: Llama 4 Maverick 17B Instruct, QwQ Plus or DeepSeek-V3?
Llama 4 Maverick 17B Instruct is the better all-round choice, scoring 63/100 against QwQ Plus (52) and DeepSeek-V3 (50). 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.
Which is cheaper, Llama 4 Maverick 17B Instruct, QwQ Plus or DeepSeek-V3?
Llama 4 Maverick 17B Instruct is cheaper at $0.321 input / $0.91 output per million tokens (median across 6 API providers). DeepSeek-V3 costs $0.32 input / $1.10 output per million tokens (median across 5 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 $0.515 for DeepSeek-V3 (1.1× as much) and $1.20 for QwQ Plus (2.6× as much).
Which scores higher on benchmarks?
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%, QwQ Plus 65.4% and DeepSeek-V3 56.5%. On individual benchmarks: GPQA Diamond — Llama 4 Maverick 17B Instruct 67.0%, QwQ Plus 65.4%, DeepSeek-V3 56.5%.
Which is better for coding?
There are no published SWE-bench Verified results for Llama 4 Maverick 17B Instruct, QwQ Plus and DeepSeek-V3 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. All three support tool calling for agent workflows.
Which has the bigger context window?
Llama 4 Maverick 17B Instruct has the largest context window at 1,000,000 tokens, against 131,072 for QwQ Plus and 131,072 for DeepSeek-V3. Maximum output per response: Llama 4 Maverick 17B Instruct up to 16,384, QwQ Plus up to 8,192, DeepSeek-V3 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama 4 Maverick 17B Instruct accepts text and images; QwQ Plus accepts text; DeepSeek-V3 accepts text. Llama 4 Maverick 17B Instruct handles the widest range of inputs.
Are any of these open source?
Llama 4 Maverick 17B Instruct and DeepSeek-V3 publishes its weights (DeepSeek Model License) and can be self-hosted; QwQ Plus is proprietary.
Which is newer?
Llama 4 Maverick 17B Instruct is the newest, released Apr 5, 2025. QwQ Plus came out Mar 5, 2025; DeepSeek-V3 came out Dec 26, 2024. Knowledge cutoff: Llama 4 Maverick 17B Instruct Aug 2024, QwQ Plus Apr 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 Oct 4, 2026.