Qwen3 8B vs Llama 4 Maverick 17B Instruct vs DeepSeek V3 0324
Too close to call on our weighted score (Llama 4 Maverick 17B Instruct 58, Qwen3 8B 56, DeepSeek V3 0324 54). The right pick depends on what you value most.
Alibaba (Qwen)
Qwen3 8B
56/100- ECI136.2
- Price$0.18 / $0.70
- Context131K
Meta
Llama 4 Maverick 17B Instruct
58/100- ECI132.2
- Price$0.321 / $0.91
- Context1M
DeepSeek
DeepSeek V3 0324
54/100- ECI135.9
- Price$0.24 / $0.90
- Context164K
Too close to call
It is close. Our weighted score puts them within 1 points (Llama 4 Maverick 17B Instruct 58/100, Qwen3 8B 56/100, DeepSeek V3 0324 54/100), so choose by what matters most for your work: Qwen3 8B for raw capability and Llama 4 Maverick 17B Instruct for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 8BCapabilities Index (ECI): Qwen3 8B 136.2 · DeepSeek V3 0324 135.9 · Llama 4 Maverick 17B Instruct 132.2
- Lowest priceQwen3 8BQwen3 8B $0.31 · DeepSeek V3 0324 $0.405 · Llama 4 Maverick 17B Instruct $0.468 per 1M tokens (3:1 blend)
- Longest contextLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct 1,000,000 · DeepSeek V3 0324 163,840 · Qwen3 8B 131,072 tokens
- Widest inputsLlama 4 Maverick 17B InstructQwen3 8B: Text · Llama 4 Maverick 17B Instruct: Text, Images · DeepSeek V3 0324: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 8B | Llama 4 Maverick 17B Instruct | DeepSeek V3 0324 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 61 | 56 | 60 |
| Price | 25% | 74 | 66 | 68 |
| Inputs & features | 15% | 35 | 50 | 25 |
| Context window | 10% | 24 | 60 | 28 |
| Overall | 100% | 56/100 | 58/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 136.2 (best) | 132.2 | 135.9 |
| ECI rank | #113 of 148 (best) | #122 of 148 | #114 of 148 |
| GPQA DiamondGraduate-level science questions | 56.8% | 67.0% | 67.6% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 56.1% (best) | 20.6% | 37.8% |
| Price per million tokens | |||
| Input | $0.18 (best) | $0.321 | $0.24 |
| Output | $0.70 (best) | $0.91 | $0.90 |
| Cached input | — | — | — |
| Blended (3:1) | $0.31 (best) | $0.468 | $0.405 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Alibaba API | Median of 6 providers | Median of 5 providers |
| Limits | |||
| Context window | 131,072 tokens | 1,000,000 tokens (best) | 163,840 tokens |
| Max output | 8,192 tokens | 16,384 tokens | 163,840 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | qwen3-8b | — | — |
| API providers | 1 | 6 (best) | 5 |
| Released | Apr 28, 2025 | Apr 5, 2025 | Mar 24, 2025 |
| Knowledge cutoff | Apr 2025 | Aug 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Qwen3 8B$3.20
Llama 4 Maverick 17B Instruct$5.03
DeepSeek V3 0324$4.20
Which should you choose?
Which is better: Qwen3 8B, Llama 4 Maverick 17B Instruct or DeepSeek V3 0324?
It is close. Our weighted score puts them within 1 points (Llama 4 Maverick 17B Instruct 58/100, Qwen3 8B 56/100, DeepSeek V3 0324 54/100), so choose by what matters most for your work: Qwen3 8B for raw capability and Llama 4 Maverick 17B Instruct for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 8B, Llama 4 Maverick 17B Instruct or DeepSeek V3 0324?
Qwen3 8B is cheaper at $0.18 input / $0.70 output per million tokens (official Alibaba API price). DeepSeek V3 0324 costs $0.24 input / $0.90 output per million tokens (median across 5 API providers); Llama 4 Maverick 17B Instruct costs $0.321 input / $0.91 output per million tokens (median across 6 API providers). At a typical mix of three input tokens to one output token, that is $0.31 per million tokens for Qwen3 8B versus $0.405 for DeepSeek V3 0324 (1.3× as much) and $0.468 for Llama 4 Maverick 17B Instruct (1.5× as much).
Which scores higher on benchmarks?
Qwen3 8B scores higher on the Capabilities Index (ECI): Qwen3 8B 136.2 (#113 of 148), DeepSeek V3 0324 135.9 (#114 of 148) and Llama 4 Maverick 17B Instruct 132.2 (#122 of 148). The confidence ranges of the top two overlap (129.7–138.1 vs 132.4–138.0), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek V3 0324 67.6%, Llama 4 Maverick 17B Instruct 67.0%, Qwen3 8B 56.8%; OTIS Mock AIME 2024–2025 — Qwen3 8B 56.1%, DeepSeek V3 0324 37.8%, Llama 4 Maverick 17B Instruct 20.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 8B, Llama 4 Maverick 17B Instruct and DeepSeek V3 0324 yet, so there is no like-for-like coding score. On overall capability, Qwen3 8B 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 163,840 for DeepSeek V3 0324 and 131,072 for Qwen3 8B. Maximum output per response: Qwen3 8B up to 8,192, Llama 4 Maverick 17B Instruct up to 16,384, DeepSeek V3 0324 up to 163,840 tokens.
Which can read images, PDFs, audio or video?
Qwen3 8B accepts text; Llama 4 Maverick 17B Instruct accepts text and images; DeepSeek V3 0324 accepts text. Llama 4 Maverick 17B Instruct handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights, so you can self-host them.
Which is newer?
Qwen3 8B is the newest, released Apr 28, 2025. Llama 4 Maverick 17B Instruct came out Apr 5, 2025; DeepSeek V3 0324 came out Mar 24, 2025. Knowledge cutoff: Qwen3 8B Apr 2025, Llama 4 Maverick 17B Instruct Aug 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.