ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Llama-3.3-70B-Instruct vs Qwen Turbo

Qwen Turbo comes out ahead, 48 to 34 on our weighted score, and it is the cheaper option too.

  1. Meta

    Llama-3.3-70B-Instruct

    Released Dec 6, 2024

    34/100
    • ECI127.3
    • Price$0.59 / $0.724
    • Context128K
    Full specs Remove Llama-3.3-70B-Instruct
  2. Our pick

    Alibaba (Qwen)

    Qwen Turbo

    Released Nov 1, 2024

    48/100
    • ECI—
    • Price$0.05 / $0.20
    • Context1M
    Full specs Remove Qwen Turbo

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen Turbo is our pick

Qwen Turbo is the better all-round choice, scoring 48/100 against Llama-3.3-70B-Instruct (34). It leads on price, inputs & features and context window. Llama-3.3-70B-Instruct wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Qwen Turbo has no Capabilities Index score yet.

  • CapabilityLlama-3.3-70B-InstructShared benchmarks: Llama-3.3-70B-Instruct 26.3% · Qwen Turbo 24.0%
  • Lowest priceQwen TurboQwen Turbo $0.087 · Llama-3.3-70B-Instruct $0.624 per 1M tokens (3:1 blend)
  • Longest contextQwen TurboQwen Turbo 1,000,000 · Llama-3.3-70B-Instruct 128,000 tokens
  • Widest inputsSame inputsLlama-3.3-70B-Instruct: Text · Qwen Turbo: Text
  • Self-hostingLlama-3.3-70B-InstructPublishes downloadable weights
How the score is built
MeasureWeightLlama-3.3-70B-InstructQwen Turbo
CapabilityShared benchmarks50%2624
Price25%60100
Inputs & features15%2535
Context window10%2460
Overall100%34/10048/100
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 Qwen Turbo specifications side by side
SpecificationLlama-3.3-70B-InstructMetaQwen TurboAlibaba (Qwen)
Capability
Capabilities Index (ECI)127.3—
ECI rank#133 of 148—
GPQA DiamondGraduate-level science questions47.4% (best)41.8%
OTIS Mock AIME 2024–2025Competition mathematics5.1%6.1% (best)
Price per million tokens
Input$0.59$0.05 (best)
Output$0.724$0.20 (best)
Cached input——
Blended (3:1)$0.624$0.087 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 21 providersOfficial Alibaba API
Limits
Context window128,000 tokens1,000,000 tokens (best)
Max output4,096 tokens16,384 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenProprietary
API model IDllama-3.3-70b-instructqwen-turbo
API providers24 (best)3
ReleasedDec 6, 2024Nov 1, 2024
Knowledge cutoffDec 2023Apr 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.

  • Llama-3.3-70B-Instruct$7.35
  • Qwen Turbo$0.90
04 — Questions

Which should you choose?

Which is better: Llama-3.3-70B-Instruct or Qwen Turbo?

Qwen Turbo is the better all-round choice, scoring 48/100 against Llama-3.3-70B-Instruct (34). It leads on price, inputs & features and context window. Llama-3.3-70B-Instruct wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Qwen Turbo has no Capabilities Index score yet.

Which is cheaper, Llama-3.3-70B-Instruct or Qwen Turbo?

Qwen Turbo is cheaper at $0.05 input / $0.20 output per million tokens (official Alibaba API price). 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 $0.087 per million tokens for Qwen Turbo versus $0.624 for Llama-3.3-70B-Instruct (7.1× 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 and OTIS Mock AIME 2024–2025): Llama-3.3-70B-Instruct 26.3% and Qwen Turbo 24.0%. On individual benchmarks: GPQA Diamond — Llama-3.3-70B-Instruct 47.4%, Qwen Turbo 41.8%; OTIS Mock AIME 2024–2025 — Qwen Turbo 6.1%, 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 Qwen Turbo yet, so there is no like-for-like coding score. On overall capability, Llama-3.3-70B-Instruct 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?

Qwen Turbo has the largest context window at 1,000,000 tokens, against 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Llama-3.3-70B-Instruct up to 4,096, Qwen Turbo up to 16,384 tokens.

Which can read images, PDFs, audio or video?

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

Are any of these open source?

Llama-3.3-70B-Instruct publishes its weights and can be self-hosted; Qwen Turbo is proprietary.

Which is newer?

Llama-3.3-70B-Instruct is the newest, released Dec 6, 2024. Qwen Turbo came out Nov 1, 2024. Knowledge cutoff: Llama-3.3-70B-Instruct Dec 2023, Qwen Turbo 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.

05 — Keep comparing

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