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Compare / head-to-head

Llama 3.3 70B InstructvsQwen3.7-Plus

Qwen3.7-Plus leads 3 of 3 shared benchmarks. Qwen3.7-Plus has the larger context window (1M tokens).

Benchmarks from cited public sources; pricing from official pages; status from official provider feeds.

Shared benchmarks
0 – 3
Qwen3.7-Plus leads
Cheaper per token
list price, input + output
Larger context
Qwen3.7-Plus
1M tokens
Provider uptime (30d)
— · —
Meta · Qwen
Llama 3.3 70B Instruct
Meta · released 2024-12-06
text
Context
131K
Max out
Input /1M
Output /1M
Cached /1M
Scores
5 · 4 core
Qwen3.7-Plus
Qwen · released 2026-05-26
textvision
Context
1M
Max out
Input /1M
$0.276
Output /1M
$1.1
Cached /1M
Scores
3 · 3 core
Quality

Benchmark matrix

BenchmarkLlama 3.3 70B InstructQwen3.7-PlusΔEdge
Reported by both · 3
GPQA Diamond50.5% 87.9% epoch-37.4 ptQwen3.7-Plus
LMArena Elo1274 1454.2 -180.2Qwen3.7-Plus
OTIS Mock AIME 2024-2025 (Epoch AI run)5.1% epoch93.3% epoch-88.2 ptQwen3.7-Plus
Only Llama 3.3 70B Instruct reports · 1
MMLU-Pro68.9% not reported
Only Qwen3.7-Plus reports · 0
Qwen3.7-Plus reports nothing Llama 3.3 70B Instruct does not.
Scores tagged "epoch" or "matharena" are independent runs, used only where the lab has not published its own; ⚠ marks rows MathArena flags as released after the competition. Higher is better on every row. Δ is Llama 3.3 70B Instruct minus Qwen3.7-Plus in the benchmark's own unit. "Not reported" means the lab has not published that figure; it is not a zero. ↗ opens the source.
Specs & pricing

Side by side

SpecLlama 3.3 70B InstructQwen3.7-PlusEdge
Context window131K tokens1M tokensQwen3.7-Plus
Max output
Input price / 1M$0.276
Output price / 1M$1.1
Cached input / 1M
Input + output / 1M
Lower is cheaper. List prices; batch, tool and regional fees excluded.
$1.38
Modalitiestexttext · visionQwen3.7-Plus
Released2024-12-062026-05-26
Cited benchmark scores53
Reliability

Provider status

All providers
More matchups

Llama 3.3 70B Instruct vs …

More matchups

Qwen3.7-Plus vs …

Built by Respan
Which one wins on your data?

Public benchmarks are a starting point. Run Llama 3.3 70B Instruct and Qwen3.7-Plus on your own prompts with Respan evals, or route to either through one gateway key with automatic failover.