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Comparison · 2 models · Updated Oct 4, 2026

Llama-3.3-70B-Instruct vs DeepSeek-V3

DeepSeek-V3 comes out ahead, 50 to 46 on our weighted score, and it is the cheaper option too.

  1. Meta

    Llama-3.3-70B-Instruct

    Released Dec 6, 2024

    46/100
    • ECI127.3
    • Price$0.59 / $0.724
    • Context128K
    Full specs Remove Llama-3.3-70B-Instruct
  2. Our pick

    DeepSeek

    DeepSeek-V3

    Released Dec 26, 2024

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

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

DeepSeek-V3 is our pick

DeepSeek-V3 is the better all-round choice, scoring 50/100 against Llama-3.3-70B-Instruct (46). It leads on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityDeepSeek-V3Capabilities Index (ECI): DeepSeek-V3 132.3 · Llama-3.3-70B-Instruct 127.3
  • Lowest priceDeepSeek-V3DeepSeek-V3 $0.515 · Llama-3.3-70B-Instruct $0.624 per 1M tokens (3:1 blend)
  • Longest contextDeepSeek-V3DeepSeek-V3 131,072 · Llama-3.3-70B-Instruct 128,000 tokens
  • Widest inputsSame inputsLlama-3.3-70B-Instruct: Text · DeepSeek-V3: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightLlama-3.3-70B-InstructDeepSeek-V3
CapabilityCapabilities Index (ECI)50%4956
Price25%6064
Inputs & features15%2525
Context window10%2424
Overall100%46/10050/100
02 — Side by side

Every spec in one table

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

Llama-3.3-70B-Instruct vs DeepSeek-V3 specifications side by side
SpecificationLlama-3.3-70B-InstructMetaDeepSeek-V3DeepSeek
Capability
Capabilities Index (ECI)127.3132.3 (best)
ECI rank#133 of 148#121 of 148 (best)
GPQA DiamondGraduate-level science questions47.4%56.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics5.1%15.8% (best)
Price per million tokens
Input$0.59$0.32 (best)
Output$0.724 (best)$1.10
Cached input——
Blended (3:1)$0.624$0.515 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 21 providersMedian of 5 providers
Limits
Context window128,000 tokens131,072 tokens (best)
Max output4,096 tokens8,192 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpenDeepSeek Model License
API model IDllama-3.3-70b-instruct—
API providers24 (best)5
ReleasedDec 6, 2024Dec 26, 2024
Knowledge cutoffDec 2023—
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.

  • Llama-3.3-70B-Instruct$7.35
  • DeepSeek-V3$5.40
04 — Questions

Which should you choose?

Which is better: Llama-3.3-70B-Instruct or DeepSeek-V3?

DeepSeek-V3 is the better all-round choice, scoring 50/100 against Llama-3.3-70B-Instruct (46). It leads on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama-3.3-70B-Instruct or DeepSeek-V3?

DeepSeek-V3 is cheaper at $0.32 input / $1.10 output per million tokens (median across 5 API providers). Llama-3.3-70B-Instruct costs $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama). At a typical mix of three input tokens to one output token, that is $0.515 per million tokens for DeepSeek-V3 versus $0.624 for Llama-3.3-70B-Instruct (1.2× 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-3.3-70B-Instruct 127.3 (#133 of 148). The confidence ranges of the top two overlap (127.5–135.5 vs 122.5–129.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek-V3 56.5%, Llama-3.3-70B-Instruct 47.4%; OTIS Mock AIME 2024–2025 — DeepSeek-V3 15.8%, Llama-3.3-70B-Instruct 5.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.3-70B-Instruct and DeepSeek-V3 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?

DeepSeek-V3 has the largest context window at 131,072 tokens, against 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Llama-3.3-70B-Instruct up to 4,096, DeepSeek-V3 up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Llama-3.3-70B-Instruct accepts text; DeepSeek-V3 accepts text. They handle the same number of input types.

Are any of these open source?

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

Which is newer?

DeepSeek-V3 is the newest, released Dec 26, 2024. Llama-3.3-70B-Instruct came out Dec 6, 2024. Knowledge cutoff: Llama-3.3-70B-Instruct Dec 2023.

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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