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Comparison · 3 models · Updated Oct 4, 2026

Qwen3 8B vs Llama 4 Scout 17B Instruct vs DeepSeek V3 0324

Llama 4 Scout 17B Instruct comes out ahead, 62 to 56 and 54 on our weighted score, though Qwen3 8B is 9% cheaper per token.

  1. Alibaba (Qwen)

    Qwen3 8B

    Released Apr 28, 2025

    56/100
    • ECI136.2
    • Price$0.18 / $0.70
    • Context131K
    Full specs Remove Qwen3 8B
  2. Our pick

    Meta

    Llama 4 Scout 17B Instruct

    Released Apr 5, 2025

    62/100
    • ECI129.7
    • Price$0.225 / $0.69
    • Context10M
    Full specs Remove Llama 4 Scout 17B Instruct

  3. DeepSeek

    DeepSeek V3 0324

    Released Mar 24, 2025

    54/100
    • ECI135.9
    • Price$0.24 / $0.90
    • Context164K
    Full specs Remove DeepSeek V3 0324
01 — Verdict

Llama 4 Scout 17B Instruct is our pick

Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Qwen3 8B (56) and DeepSeek V3 0324 (54). It leads on inputs & features and context window. Qwen3 8B wins on price. 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 Scout 17B Instruct 129.7
  • Lowest priceQwen3 8BQwen3 8B $0.31 · Llama 4 Scout 17B Instruct $0.341 · DeepSeek V3 0324 $0.405 per 1M tokens (3:1 blend)
  • Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · DeepSeek V3 0324 163,840 · Qwen3 8B 131,072 tokens
  • Widest inputsLlama 4 Scout 17B InstructQwen3 8B: Text · Llama 4 Scout 17B Instruct: Text, Images · DeepSeek V3 0324: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3 8BLlama 4 Scout 17B InstructDeepSeek V3 0324
CapabilityCapabilities Index (ECI)50%615260
Price25%747268
Inputs & features15%355025
Context window10%2410028
Overall100%56/10062/10054/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Qwen3 8B vs Llama 4 Scout 17B Instruct vs DeepSeek V3 0324 specifications side by side
SpecificationQwen3 8BAlibaba (Qwen)Llama 4 Scout 17B InstructMetaDeepSeek V3 0324DeepSeek
Capability
Capabilities Index (ECI)136.2 (best)129.7135.9
ECI rank#113 of 148 (best)#126 of 148#114 of 148
GPQA DiamondGraduate-level science questions56.8%51.8%67.6% (best)
OTIS Mock AIME 2024–2025Competition mathematics56.1% (best)7.8%37.8%
Price per million tokens
Input$0.18 (best)$0.225$0.24
Output$0.70$0.69 (best)$0.90
Cached input———
Blended (3:1)$0.31 (best)$0.341$0.405
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIMedian of 4 providersMedian of 5 providers
Limits
Context window131,072 tokens10,000,000 tokens (best)163,840 tokens
Max output8,192 tokens16,384 tokens163,840 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model IDqwen3-8b——
API providers145 (best)
ReleasedApr 28, 2025Apr 5, 2025Mar 24, 2025
Knowledge cutoffApr 2025Aug 2024—
03 — Cost

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 Scout 17B Instruct$3.63
  • DeepSeek V3 0324$4.20
04 — Questions

Which should you choose?

Which is better: Qwen3 8B, Llama 4 Scout 17B Instruct or DeepSeek V3 0324?

Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Qwen3 8B (56) and DeepSeek V3 0324 (54). It leads on inputs & features and context window. Qwen3 8B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen3 8B, Llama 4 Scout 17B Instruct or DeepSeek V3 0324?

Qwen3 8B is cheaper at $0.18 input / $0.70 output per million tokens (official Alibaba API price). Llama 4 Scout 17B Instruct costs $0.225 input / $0.69 output per million tokens (median across 4 API providers); DeepSeek V3 0324 costs $0.24 input / $0.90 output per million tokens (median across 5 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 $0.341 for Llama 4 Scout 17B Instruct (1.1× as much) and $0.405 for DeepSeek V3 0324 (1.3× 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 Scout 17B Instruct 129.7 (#126 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%, Qwen3 8B 56.8%, Llama 4 Scout 17B Instruct 51.8%; OTIS Mock AIME 2024–2025 — Qwen3 8B 56.1%, DeepSeek V3 0324 37.8%, Llama 4 Scout 17B Instruct 7.8%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 8B, Llama 4 Scout 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 Scout 17B Instruct has the largest context window at 10,000,000 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 Scout 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 Scout 17B Instruct accepts text and images; DeepSeek V3 0324 accepts text. Llama 4 Scout 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 Scout 17B Instruct came out Apr 5, 2025; DeepSeek V3 0324 came out Mar 24, 2025. Knowledge cutoff: Qwen3 8B Apr 2025, Llama 4 Scout 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.

05 — Keep comparing

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