Pairwise benchmark snapshot · Aug 1, 2026

Gemini 2.0 Flash Thinking vs Llama 3.1 405B benchmark

Name: Gemini 2.0 Flash Thinking vs Llama 3.1 405B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Gemini 2.0 Flash Thinking (Google) and Llama 3.1 405B (Meta) using the latest snapshots we have as of Aug 1, 2026. On preference Elo, Gemini 2.0 Flash Thinking is ahead by 120 points (1,490 vs 1,370; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Gemini 2.0 Flash Thinking resolves 66.8% versus 58.4% (seed-bootstrap (Aug 1, 2026)). Gemini 2.0 Flash Thinking streams faster (115 tok/s) while Gemini 2.0 Flash Thinking is the cheaper output token ($0.4/1M). Gemini 2.0 Flash Thinking has the larger context window (1M 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 2.0 Flash Thinking

Google experimental reasoning model that visualizes thoughts in real-time.

Elo 1,490$0.4/1M out

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Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 2.0 Flash Thinking (10)vsLlama 3.1 405B (0)

Gemini 2.0 Flash Thinking: 10W (100%)Overall: Gemini 2.0 Flash ThinkingLlama 3.1 405B: 0W (0%)

← Gemini 2.0 Flash ThinkingLlama 3.1 405B →

Gemini 2.0 Flash Thinking (5/5)

Intelligence & Reasoning

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

Preference Elo

1,490vs1,370

Coding Elo

1,515vs1,385

SWE-bench

66.8%vs58.4%

LiveBench

67%vs61.2%

GPQA Diamond

81%vs75.2%

Gemini 2.0 Flash Thinking: 5WLlama 3.1 405B: 0W

Gemini 2.0 Flash Thinking (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

115 tok/svs42 tok/s

Time to first token

220 msvs360 ms

Gemini 2.0 Flash Thinking: 2WLlama 3.1 405B: 0W

Gemini 2.0 Flash Thinking (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.4/1Mvs$3.5/1M

Input price

$0.1/1Mvs$1.25/1M

Context window

1Mvs128k

Gemini 2.0 Flash Thinking: 3WLlama 3.1 405B: 0W

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 2.0 Flash Thinking 6/6

Preference Elo

Gemini 2.0 Flash Thinking

120 pts advantage

Throughput Speed

Gemini 2.0 Flash Thinking

73 tok/s faster

Price Efficiency

Gemini 2.0 Flash Thinking

$3.10/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+9%1,490

EloHigh is better

1,370

Code Elo

High is better

+9%1,515

Code EloHigh is better

1,385

LiveBench

High is better

+9%67%

LiveBenchHigh is better

61.2%

SWE-bench

High is better

+14%66.8%

SWE-benchHigh is better

58.4%

GPQA

High is better

+8%81%

GPQAHigh is better

75.2%

TTFT

Low is better

+64%220 ms

TTFTLow is better

360 ms

Speed

High is better

+174%115 tok/s

SpeedHigh is better

42 tok/s

In $

Low is better

+1150%$0.1/1M

In $Low is better

$1.25/1M

Out $

Low is better

+775%$0.4/1M

Out $Low is better

$3.5/1M

Context

High is better

+719%1M

ContextHigh is better

128k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 90% with Gemini 2.0 Flash Thinking

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Gemini 2.0 Flash Thinking$9.50 / mo

In: $3.50Out: $6.00

Llama 3.1 405B$96.25 / mo

In: $43.75Out: $52.50

Estimated Cost Delta

Gemini 2.0 Flash Thinking is estimated to save $86.75/month ($1,041/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Gemini 2.0 Flash Thinking:Pick Gemini 2.0 Flash Thinking when repo-level coding accuracy is the constraint.
2
Gemini 2.0 Flash Thinking:Pick Gemini 2.0 Flash Thinking when time-to-first-token matters more than peak Elo.
3
Gemini 2.0 Flash Thinking:Pick Gemini 2.0 Flash Thinking for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsGemini 2.0 Flash Thinking

Higher SWE-bench (66.8%).

High-volume chatGemini 2.0 Flash Thinking

Lower output list price ($0.4/1M).

Voice / low-latency UIGemini 2.0 Flash Thinking

Lower TTFT (220 ms).

Long-document RAGGemini 2.0 Flash Thinking

Larger window (1M).

Screenshots / visionGemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Gemini 2.0 Flash Thinking	Higher SWE-bench (66.8%).
High-volume chat	Gemini 2.0 Flash Thinking	Lower output list price ($0.4/1M).
Voice / low-latency UI	Gemini 2.0 Flash Thinking	Lower TTFT (220 ms).
Long-document RAG	Gemini 2.0 Flash Thinking	Larger window (1M).
Screenshots / vision	Gemini 2.0 Flash Thinking	Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

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LIVE

Google

Gemini 2.0 Flash Thinking

Elo 1,490

LiveBench67%

SWE-bench66.8%

Speed115 tok/s

Output cost$0.4/1M

Llama 3.1 405B

Elo 1,370

LiveBench61.2%

SWE-bench58.4%

Speed42 tok/s

Output cost$3.5/1M

Frequently Asked Questions

Which is better overall, Gemini 2.0 Flash Thinking or Llama 3.1 405B?: Gemini 2.0 Flash Thinking has the higher preference Elo in our latest snapshot (1,490). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Gemini 2.0 Flash Thinking or Llama 3.1 405B?: Gemini 2.0 Flash Thinking leads SWE-bench at 66.8% vs 58.4%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Gemini 2.0 Flash Thinking output tokens are $0.4/1M versus $3.5/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 2.0 Flash Thinking or Llama 3.1 405B?: Gemini 2.0 Flash Thinking has the lower time-to-first-token (220 ms vs 360 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Gemini 2.0 Flash Thinking accepts 1M tokens versus 128k.
Can I self-host either model?: Llama 3.1 405B 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 2.0 Flash Thinking and Llama 3.1 405B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Gemini 2.0 Flash Thinking matchups →|All Llama 3.1 405B matchups →

Gemini 2.0 Flash Thinking vs Gemini 2.5 Flash (next gemini-flash)Llama 3.1 405B vs Llama 3.1 70B (next llama)Gemini 3 Flash vs Gemini 2.0 Flash Thinking Gemini 3.6 Flash vs Gemini 2.0 Flash Thinking Llama 4 Maverick vs Gemini 2.0 Flash Thinking Gemini 3.7 Flash vs Gemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking vs Llama 3.1 405B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Gemini 2.0 Flash Thinking (10)vsLlama 3.1 405B (0)

Gemini 2.0 Flash Thinking: 10W (100%)Overall: Gemini 2.0 Flash ThinkingLlama 3.1 405B: 0W (0%)

← Gemini 2.0 Flash ThinkingLlama 3.1 405B →

Gemini 2.0 Flash Thinking (5/5)

Intelligence & Reasoning

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

Preference Elo

1,490vs1,370

Coding Elo

1,515vs1,385

SWE-bench

66.8%vs58.4%

LiveBench

67%vs61.2%

GPQA Diamond

81%vs75.2%

Gemini 2.0 Flash Thinking: 5WLlama 3.1 405B: 0W

Gemini 2.0 Flash Thinking (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

115 tok/svs42 tok/s

Time to first token

220 msvs360 ms

Gemini 2.0 Flash Thinking: 2WLlama 3.1 405B: 0W

Gemini 2.0 Flash Thinking (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.4/1Mvs$3.5/1M

Input price

$0.1/1Mvs$1.25/1M

Context window

1Mvs128k

Gemini 2.0 Flash Thinking: 3WLlama 3.1 405B: 0W

Recommended Workload Routing

Repo / coding agentsGemini 2.0 Flash Thinking

Higher SWE-bench (66.8%).

High-volume chatGemini 2.0 Flash Thinking

Lower output list price ($0.4/1M).

Voice / low-latency UIGemini 2.0 Flash Thinking

Lower TTFT (220 ms).

Long-document RAGGemini 2.0 Flash Thinking

Larger window (1M).

Screenshots / visionGemini 2.0 Flash Thinking

Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Gemini 2.0 Flash Thinking	Higher SWE-bench (66.8%).
High-volume chat	Gemini 2.0 Flash Thinking	Lower output list price ($0.4/1M).
Voice / low-latency UI	Gemini 2.0 Flash Thinking	Lower TTFT (220 ms).
Long-document RAG	Gemini 2.0 Flash Thinking	Larger window (1M).
Screenshots / vision	Gemini 2.0 Flash Thinking	Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Gemini 2.0 Flash Thinking or Llama 3.1 405B?

Gemini 2.0 Flash Thinking has the higher preference Elo in our latest snapshot (1,490). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Gemini 2.0 Flash Thinking or Llama 3.1 405B?

Gemini 2.0 Flash Thinking leads SWE-bench at 66.8% vs 58.4%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Gemini 2.0 Flash Thinking output tokens are $0.4/1M versus $3.5/1M. Input prices and retry rates still move the real bill.

Which is faster, Gemini 2.0 Flash Thinking or Llama 3.1 405B?

Gemini 2.0 Flash Thinking has the lower time-to-first-token (220 ms vs 360 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Gemini 2.0 Flash Thinking accepts 1M tokens versus 128k.

Can I self-host either model?

Llama 3.1 405B 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 2.0 Flash Thinking and Llama 3.1 405B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.