AI Models · Compare

Llama 3.3 70B vs Qwen 2.5 72B

Which AI model is better in 2026? Compare Llama 3.3 70B and Qwen 2.5 72B on benchmarks, pricing, speed, context window, and real-world fit.

Quick summary

Llama 3.3 70B is currently the stronger overall pick for reasoning, coding, speed, and price. Qwen 2.5 72B wins on math. Llama 3.3 70B is also cheaper on blended API price ($0.27 vs $0.40 / 1M).

Overall winner

Llama 3.3 70B

View Llama 3.3 70B review

Llama 3.3 70B wins

  • Reasoning
  • Coding
  • Speed
  • Price

Qwen 2.5 72B wins

  • Math

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Meta

Llama 3.3 70B

Open sourceDec 2024

Open-weights 70B that matches GPT-4o on most benchmarks.

Open docs
Alibaba

Qwen 2.5 72B

Open sourceSep 2024

Apache 2.0 open weights — strong multilingual + math.

Open docs

Llama 3.3 70B vs Qwen 2.5 72B: overview

Llama 3.3 70B (Meta) and Qwen 2.5 72B (Alibaba) are frequently compared by teams choosing an AI stack in 2026. Llama 3.3 70B: Open-weights 70B that matches GPT-4o on most benchmarks. Qwen 2.5 72B: Apache 2.0 open weights — strong multilingual + math. This Llama 3.3 70B vs Qwen 2.5 72B comparison covers benchmarks, pricing, context window, speed, modalities, strengths, weaknesses, and who should pick which model.

Llama 3.3 70B is open-weights with a 128k-token context window and a blended API price near $0.27 / 1M tokens (intelligence index 66/100). Qwen 2.5 72B is open-weights with 128k context at about $0.40 blended / 1M (intelligence 62/100). Those gaps drive most “Llama 3.3 70B vs Qwen 2.5 72B” searches — quality versus cost, closed versus open, cloud versus self-host.

Where they differ most: Llama 3.3 70B tends to lead on reasoning, coding, speed, and price, while Qwen 2.5 72B leads on math. Choose Llama 3.3 70B when you want the stronger overall profile on our scorecard; validate with your own evals before migrating production traffic.

Llama 3.3 70B is often shortlisted for self-hosting, eu data residency, and cost-sensitive workloads. Qwen 2.5 72B fits self-hosting and chinese / multilingual apps. Scroll to pricing, real-world tasks, and the who-should-choose section for decision support.

People search “Llama 3.3 70B vs Qwen 2.5 72B”, “which is better”, and “Llama 3.3 70B vs Qwen 2.5 72B pricing” for the same reason: switching models is expensive if quality drops, and staying put is expensive if you overpay. Use the winner card for a fast answer, the head-to-head table for receipts, and the editorial verdict for a human recommendation. Llama 3.3 70B currently ranks among frontier options from Meta; Qwen 2.5 72B is a flexible open-weights alternative from Alibaba. If API pricing is your main concern, start with the pricing section; for multimodal workloads, check vision/audio rows in technical differences; for agents and long documents, prioritize context and reasoning wins.

Head to head

Spec
Llama 3.3 70B
Qwen 2.5 72B
Winner
Reason
Intelligence index↑ better
Winner66
62
Llama 3.3 70B
Llama 3.3 70B leads on the composite intelligence index (66 vs 62).
Speed↑ better
Winner200 tok/s
55 tok/s
Llama 3.3 70B
Llama 3.3 70B generates tokens faster (200 vs 55 tok/s).
Time to first token↓ better
Winner0.4 s
0.5 s
Llama 3.3 70B
Llama 3.3 70B starts streaming sooner (0.4s vs 0.5s TTFT).
Context window↑ better
128k
128k
Tie
Even — no meaningful gap in our catalog.
Max output↑ better
4k
Winner8k
Qwen 2.5 72B
Qwen 2.5 72B wins this row (8192 vs 4096).
Input price↓ better
Winner$0.23 / 1M tokens
$0.40 / 1M tokens
Llama 3.3 70B
Llama 3.3 70B is cheaper (~1.7× lower on this price row).
Output price↓ better
$0.40 / 1M tokens
$0.40 / 1M tokens
Tie
Even — no meaningful gap in our catalog.
Blended price↓ better
Winner$0.27 / 1M tokens
$0.40 / 1M tokens
Llama 3.3 70B
Llama 3.3 70B is cheaper (~1.5× lower on this price row).
License
Open source
Open source
Qualitative / categorical row
Input modalities
text
text
Qualitative / categorical row
Output modalities
text
text
Qualitative / categorical row

Pricing comparison

API cost is often the deciding factor in Llama 3.3 70B vs Qwen 2.5 72B for high-volume apps. Figures below use catalog list prices with a 3:1 input:output blend for monthly estimates. Cached input, batch, and realtime surcharges vary by provider — confirm on official docs.

API costLlama 3.3 70BQwen 2.5 72B
Input / 1M tokens$0.23$0.40
Output / 1M tokens$0.40$0.40
Blended (3:1) / 1M$0.27$0.40
Est. cost @ 1M blended tokens$0.27$0.40
Est. cost @ 10M blended tokens$2.70$4.00
Est. cost @ 100M blended tokens$27.00$40.00

Cached input, batch API, and realtime surcharges are provider-specific and not always published in our catalog — verify on official pricing pages.

Benchmark showdown

MMLU
Llama 3.3 70B
86.0
Qwen 2.5 72B
85.3
MMLU Pro
Llama 3.3 70B
68.9
Qwen 2.5 72B
71.1
GPQA
Llama 3.3 70B
50.5
Qwen 2.5 72B
49.0
MATH
Llama 3.3 70B
77.0
Qwen 2.5 72B
83.1
HumanEval
Llama 3.3 70B
88.4
Qwen 2.5 72B
86.6

Llama 3.3 70B leads on MMLU, GPQA, and HumanEval, indicating stronger coding and reasoning-oriented scores. Qwen 2.5 72B leads on MMLU Pro and MATH. Llama 3.3 70B also undercuts on blended API price. Raw benchmarks shortlist models — run task-specific evals before you switch.

Real-world performance

Beyond academic scores, here is how Llama 3.3 70B vs Qwen 2.5 72B tends to split common product tasks based on catalog strengths, price, and modalities.

TaskWinner
CodingLlama 3.3 70B
Blog writingLlama 3.3 70B
ResearchLlama 3.3 70B
Customer supportLlama 3.3 70B
Cheap API / high volumeLlama 3.3 70B
AI agentsLlama 3.3 70B
SummarizationLlama 3.3 70B
TranslationLlama 3.3 70B
Vision / multimodalLlama 3.3 70B
Self-hosting / open weightsLlama 3.3 70B

Technical differences

FeatureLlama 3.3 70BQwen 2.5 72B
ProviderMetaAlibaba
LicenseOpen sourceOpen source
Pricing modeltokenstokens
Context window128k tokens128k tokens
Max output4k tokens8k tokens
Vision inputNoNo
Audio inputNoNo
Text outputYesYes
Image outputNoNo
Video outputNoNo
Audio outputNoNo
Self-host friendlyYesYes
DocsAvailableAvailable

Strengths, weaknesses and best-for

Llama 3.3 70B
Strengths
  • Open weights
  • Fast on Groq / Cerebras
  • Cheap
Weaknesses
  • No vision
  • Smaller context than peers
Best for
  • Self-hosting
  • EU data residency
  • Cost-sensitive workloads
Qwen 2.5 72B
Strengths
  • Open weights
  • Strong on Chinese
  • Great on math
Weaknesses
  • Less English fine-tuning data than Llama
Best for
  • Self-hosting
  • Chinese / multilingual apps

Who should choose which

Choose Llama 3.3 70B if

  • You need stronger reasoning, coding, or math quality
  • You care about faster token throughput
  • API budget is the top constraint
  • Self-hosting
  • EU data residency

Choose Qwen 2.5 72B if

  • You need stronger reasoning, coding, or math quality
  • Self-hosting
  • Chinese / multilingual apps

Pros & cons

Llama 3.3 70B

Pros

  • Open weights
  • Fast on Groq / Cerebras
  • Cheap

Cons

  • No vision
  • Smaller context than peers

Qwen 2.5 72B

Pros

  • Open weights
  • Strong on Chinese
  • Great on math

Cons

  • Less English fine-tuning data than Llama

Editorial verdict

Llama 3.3 70B edges this matchup — with caveats

Llama 3.3 70B is the better choice when you prioritize reasoning, coding, speed, and price. Qwen 2.5 72B stands out for math, making it a strong option when those dimensions matter more than raw leaderboard rank. If maximum measured performance matters, Llama 3.3 70B wins this matchup. If your niche constraints matter more, Qwen 2.5 72B is difficult to beat. Always confirm with a bake-off on your real prompts before cutting over.

Still deciding? Read the full Llama 3.3 70B review and Qwen 2.5 72B review, or open the full AI models table.

Llama 3.3 70B vs Qwen 2.5 72B — frequently asked questions

On our scorecard, Llama 3.3 70B wins overall (leads on Reasoning, Coding, Speed, and Price). The “better” model still depends on your workload — validate with your own evals.

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