Pairwise benchmark snapshot · Aug 16, 2026

Gemini 3.6 Pro vs Llama 3.3 70B benchmark

Name: Gemini 3.6 Pro vs Llama 3.3 70B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Gemini 3.6 Pro (Google) and Llama 3.3 70B (Meta) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, Gemini 3.6 Pro is ahead by 285 points (1,570 vs 1,285; seed-bootstrap (Aug 16, 2026)). On SWE-bench coding, Gemini 3.6 Pro resolves 74.6% versus 45.1% (seed-bootstrap (Aug 16, 2026)). Llama 3.3 70B streams faster (140 tok/s) while Llama 3.3 70B is the cheaper output token ($0.32/1M). Gemini 3.6 Pro has the larger context window (2M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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Google

Gemini 3.6 Pro

Current Google Pro-class multimodal model. Long context, strong coding, billed like the 3.x Pro tier.

Elo 1,570$5/1M out

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Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 3.6 Pro (6)vsLlama 3.3 70B (4)

Gemini 3.6 Pro: 6W (60%)Overall: Gemini 3.6 ProLlama 3.3 70B: 4W (40%)

← Gemini 3.6 ProLlama 3.3 70B →

Gemini 3.6 Pro (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,570vs1,285

Coding Elo

1,566vs—

SWE-bench

74.6%vs45.1%

LiveBench

71.8%vs49.8%

GPQA Diamond

84.4%vs65.7%

Gemini 3.6 Pro: 5WLlama 3.3 70B: 0W

Llama 3.3 70B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

102 tok/svs140 tok/s

Time to first token

205 msvs160 ms

Gemini 3.6 Pro: 0WLlama 3.3 70B: 2W

Llama 3.3 70B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$5/1Mvs$0.32/1M

Input price

$1.25/1Mvs$0.1/1M

Context window

2Mvs131k

Gemini 3.6 Pro: 1WLlama 3.3 70B: 2W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageGemini 3.6 Pro 4/6

Preference Elo

Gemini 3.6 Pro

285 pts advantage

Throughput Speed

Llama 3.3 70B

38 tok/s faster

Price Efficiency

Llama 3.3 70B

$4.68/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+22%1,570

EloHigh is better

1,285

Code Elo

High is better

1,566

Code EloHigh is better

—

LiveBench

High is better

+44%71.8%

LiveBenchHigh is better

49.8%

SWE-bench

High is better

+65%74.6%

SWE-benchHigh is better

45.1%

GPQA

High is better

+28%84.4%

GPQAHigh is better

65.7%

TTFT

Low is better

205 ms

TTFTLow is better

160 ms+28%

Speed

High is better

102 tok/s

SpeedHigh is better

140 tok/s+37%

In $

Low is better

$1.25/1M

In $Low is better

$0.1/1M+1150%

Out $

Low is better

$5/1M

Out $Low is better

$0.32/1M+1462%

Context

High is better

+1426%2M

ContextHigh is better

131k

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Save up to 93% with Llama 3.3 70B

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

Gemini 3.6 Pro$118.75 / mo

In: $43.75Out: $75.00

Llama 3.3 70B$8.30 / mo

In: $3.50Out: $4.80

Estimated Cost Delta

Llama 3.3 70B is estimated to save $110.45/month ($1,325/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Gemini 3.6 Pro:Pick Gemini 3.6 Pro when repo-level coding accuracy is the constraint.
2
Llama 3.3 70B:Pick Llama 3.3 70B when you are optimizing output cost.
3
Llama 3.3 70B:Pick Llama 3.3 70B when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsGemini 3.6 Pro

Higher SWE-bench (74.6%).

High-volume chatLlama 3.3 70B

Lower output list price ($0.32/1M).

Voice / low-latency UILlama 3.3 70B

Lower TTFT (160 ms).

Long-document RAGGemini 3.6 Pro

Larger window (2M).

Screenshots / visionGemini 3.6 Pro

Gemini 3.6 Pro is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Gemini 3.6 Pro	Higher SWE-bench (74.6%).
High-volume chat	Llama 3.3 70B	Lower output list price ($0.32/1M).
Voice / low-latency UI	Llama 3.3 70B	Lower TTFT (160 ms).
Long-document RAG	Gemini 3.6 Pro	Larger window (2M).
Screenshots / vision	Gemini 3.6 Pro	Gemini 3.6 Pro is the side marked multimodal in the catalog.

Related Editorial Dispatches & Benchmark Notes

View all news

compareAug 13, 2026

Gemini Flash vs Pro: when Flash is the whole product

3.7 Flash vs 3.6 Pro is the current Google volume-versus-upgrade pair.

compareJul 24, 2026

Claude vs Gemini: coding, Elo, and output price — not a brand mashup

Top Anthropic vs top Google. Usually Opus 5 vs 3.6 Pro. Two different invoices.

compareJul 16, 2026

Gemini vs GPT: long context versus the OpenAI flagship invoice

Hub remaps to top Google vs top OpenAI Elo. Usually 3.6 Pro vs Sol. Window vs price is the plot.

launchJul 15, 2026

Gemini 3.6 Pro: Google’s current Pro-class long-context row

2M context, Pro-class Elo and coding. Upgrade path from Flash is this page, not a vibe check.

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LIVE

Google

Gemini 3.6 Pro

Elo 1,570

LiveBench71.8%

SWE-bench74.6%

Speed102 tok/s

Output cost$5/1M

Llama 3.3 70B

Elo 1,285

LiveBench49.8%

SWE-bench45.1%

Speed140 tok/s

Output cost$0.32/1M

Frequently Asked Questions

Which is better overall, Gemini 3.6 Pro or Llama 3.3 70B?: Gemini 3.6 Pro has the higher preference Elo in our latest snapshot (1,570). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Gemini 3.6 Pro or Llama 3.3 70B?: Gemini 3.6 Pro leads SWE-bench at 74.6% vs 45.1%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Llama 3.3 70B output tokens are $0.32/1M versus $5/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 3.6 Pro or Llama 3.3 70B?: Llama 3.3 70B has the lower time-to-first-token (160 ms vs 205 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Gemini 3.6 Pro accepts 2M tokens versus 131k.
Can I self-host either model?: Llama 3.3 70B is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Gemini 3.6 Pro and Llama 3.3 70B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Gemini 3.6 Pro matchups →|All Llama 3.3 70B matchups →

Gemini 3.6 Pro vs Gemini 3 Pro (previous gemini-pro)Llama 3.3 70B vs Llama 3.1 70B (previous llama)Llama 3.3 70B vs Llama 4 Maverick (next llama)Gemini 3.7 Flash vs Gemini 3.6 Pro Gemini 3.6 Flash vs Gemini 3.6 Pro Gemini 3 Flash vs Gemini 3.6 Pro

Gemini 3.6 Pro vs Llama 3.3 70B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 3.6 Pro (6)vsLlama 3.3 70B (4)

Gemini 3.6 Pro: 6W (60%)Overall: Gemini 3.6 ProLlama 3.3 70B: 4W (40%)

← Gemini 3.6 ProLlama 3.3 70B →

Gemini 3.6 Pro (5/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

1,570vs1,285

Coding Elo

1,566vs—

SWE-bench

74.6%vs45.1%

LiveBench

71.8%vs49.8%

GPQA Diamond

84.4%vs65.7%

Gemini 3.6 Pro: 5WLlama 3.3 70B: 0W

Llama 3.3 70B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

102 tok/svs140 tok/s

Time to first token

205 msvs160 ms

Gemini 3.6 Pro: 0WLlama 3.3 70B: 2W

Llama 3.3 70B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$5/1Mvs$0.32/1M

Input price

$1.25/1Mvs$0.1/1M

Context window

2Mvs131k

Gemini 3.6 Pro: 1WLlama 3.3 70B: 2W

Recommended Workload Routing

Repo / coding agentsGemini 3.6 Pro

Higher SWE-bench (74.6%).

High-volume chatLlama 3.3 70B

Lower output list price ($0.32/1M).

Voice / low-latency UILlama 3.3 70B

Lower TTFT (160 ms).

Long-document RAGGemini 3.6 Pro

Larger window (2M).

Screenshots / visionGemini 3.6 Pro

Gemini 3.6 Pro is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Gemini 3.6 Pro	Higher SWE-bench (74.6%).
High-volume chat	Llama 3.3 70B	Lower output list price ($0.32/1M).
Voice / low-latency UI	Llama 3.3 70B	Lower TTFT (160 ms).
Long-document RAG	Gemini 3.6 Pro	Larger window (2M).
Screenshots / vision	Gemini 3.6 Pro	Gemini 3.6 Pro is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Gemini 3.6 Pro or Llama 3.3 70B?

Gemini 3.6 Pro has the higher preference Elo in our latest snapshot (1,570). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Gemini 3.6 Pro or Llama 3.3 70B?

Gemini 3.6 Pro leads SWE-bench at 74.6% vs 45.1%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Llama 3.3 70B output tokens are $0.32/1M versus $5/1M. Input prices and retry rates still move the real bill.

Which is faster, Gemini 3.6 Pro or Llama 3.3 70B?

Llama 3.3 70B has the lower time-to-first-token (160 ms vs 205 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Gemini 3.6 Pro accepts 2M tokens versus 131k.

Can I self-host either model?

Llama 3.3 70B is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Gemini 3.6 Pro and Llama 3.3 70B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

Gemini 3.6 Pro

Llama 3.3 70B

Llama 3.3 70B

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Gemini Flash vs Pro: when Flash is the whole product

Claude vs Gemini: coding, Elo, and output price — not a brand mashup

Gemini vs GPT: long context versus the OpenAI flagship invoice

Gemini 3.6 Pro: Google’s current Pro-class long-context row

Cast Your Matchup Vote

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CompareLLM Matrix

Gemini 3.6 Pro

Llama 3.3 70B

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons

Swap or Add Any Model to this Matchup

Interactive Comparison Diagram

Tug-of-War Matchup Matrix

Intelligence & Reasoning

Speed & Latency

Pricing & Capacity

Multi-Dimensional Capability Radar

Gemini 3.6 Pro

Llama 3.3 70B

Llama 3.3 70B

Full Benchmark Score Matrix

Workload Cost & Savings Calculator

Key Selection Recommendations

Recommended Workload Routing

Related Editorial Dispatches & Benchmark Notes

Gemini Flash vs Pro: when Flash is the whole product

Claude vs Gemini: coding, Elo, and output price — not a brand mashup

Gemini vs GPT: long context versus the OpenAI flagship invoice

Gemini 3.6 Pro: Google’s current Pro-class long-context row

Cast Your Matchup Vote

Community Discussions (0)

Share card

CompareLLM Matrix

Gemini 3.6 Pro

Llama 3.3 70B

Frequently Asked Questions

Related news

Similar Head-to-Head Comparisons