ZMIME
Comparison · 2 models · Updated Oct 4, 2026

DeepSeek-V3 vs Llama 4 Scout 17B Instruct

Llama 4 Scout 17B Instruct comes out ahead, 62 to 50 on our weighted score, and it is the cheaper option too.

  1. DeepSeek

    DeepSeek-V3

    Released Dec 26, 2024

    50/100
    • ECI132.3
    • Price$0.32 / $1.10
    • Context131K
    Full specs Remove DeepSeek-V3
  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. Add a model

    Make it a three-way comparison.

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 DeepSeek-V3 (50). It leads on price, inputs & features and context window. DeepSeek-V3 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityDeepSeek-V3Capabilities Index (ECI): DeepSeek-V3 132.3 · Llama 4 Scout 17B Instruct 129.7
  • Lowest priceLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct $0.341 · DeepSeek-V3 $0.515 per 1M tokens (3:1 blend)
  • Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · DeepSeek-V3 131,072 tokens
  • Widest inputsLlama 4 Scout 17B InstructDeepSeek-V3: Text · Llama 4 Scout 17B Instruct: Text, Images
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightDeepSeek-V3Llama 4 Scout 17B Instruct
CapabilityCapabilities Index (ECI)50%5652
Price25%6472
Inputs & features15%2550
Context window10%24100
Overall100%50/10062/100
02 — Side by side

Every spec in one table

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

DeepSeek-V3 vs Llama 4 Scout 17B Instruct specifications side by side
SpecificationDeepSeek-V3DeepSeekLlama 4 Scout 17B InstructMeta
Capability
Capabilities Index (ECI)132.3 (best)129.7
ECI rank#121 of 148 (best)#126 of 148
GPQA DiamondGraduate-level science questions56.5% (best)51.8%
OTIS Mock AIME 2024–2025Competition mathematics15.8% (best)7.8%
Price per million tokens
Input$0.32$0.225 (best)
Output$1.10$0.69 (best)
Cached input——
Blended (3:1)$0.515$0.341 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 5 providersMedian of 4 providers
Limits
Context window131,072 tokens10,000,000 tokens (best)
Max output8,192 tokens16,384 tokens (best)
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenDeepSeek Model LicenseOpen
API model ID——
API providers5 (best)4
ReleasedDec 26, 2024Apr 5, 2025
Knowledge cutoff—Aug 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.

  • DeepSeek-V3$5.40
  • Llama 4 Scout 17B Instruct$3.63
04 — Questions

Which should you choose?

Which is better: DeepSeek-V3 or Llama 4 Scout 17B Instruct?

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

Which is cheaper, DeepSeek-V3 or Llama 4 Scout 17B Instruct?

Llama 4 Scout 17B Instruct is cheaper at $0.225 input / $0.69 output per million tokens (median across 4 API providers). DeepSeek-V3 costs $0.32 input / $1.10 output per million tokens (median across 5 API providers). At a typical mix of three input tokens to one output token, that is $0.341 per million tokens for Llama 4 Scout 17B Instruct versus $0.515 for DeepSeek-V3 (1.5× as much).

Which scores higher on benchmarks?

DeepSeek-V3 scores higher on the Capabilities Index (ECI): DeepSeek-V3 132.3 (#121 of 148) and Llama 4 Scout 17B Instruct 129.7 (#126 of 148). The confidence ranges of the top two overlap (127.5–135.5 vs 124.8–131.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-V3 56.5%, Llama 4 Scout 17B Instruct 51.8%; OTIS Mock AIME 2024–2025 — DeepSeek-V3 15.8%, Llama 4 Scout 17B Instruct 7.8%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-V3 and Llama 4 Scout 17B Instruct yet, so there is no like-for-like coding score. On overall capability, DeepSeek-V3 leads, which tends to carry over to coding, but test on your own codebase. Both 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 131,072 for DeepSeek-V3. Maximum output per response: DeepSeek-V3 up to 8,192, Llama 4 Scout 17B Instruct up to 16,384 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-V3 accepts text; Llama 4 Scout 17B Instruct accepts text and images. Llama 4 Scout 17B Instruct handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights (DeepSeek Model License), so you can self-host them.

Which is newer?

Llama 4 Scout 17B Instruct is the newest, released Apr 5, 2025. DeepSeek-V3 came out Dec 26, 2024. Knowledge cutoff: 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

Related comparisons