Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Google: Gemma 4 26B A4B (free) vs Llama 3.1 405B benchmark

Name: Google: Gemma 4 26B A4B (free) vs Llama 3.1 405B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

In this head-to-head showdown, Google: Gemma 4 26B A4B (free) is more budget-friendly at $0/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

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Executive Verdict Summary

Google: Gemma 4 26B A4B (free) holds empirical advantage (3 of 3 metrics)

Coding / SWESWE-bench

Llama 3.1 405BTop code solve rate

ReasoningGPQA / Live

Llama 3.1 405BTop logical accuracy

Best Value$/1M Tok

Llama 3.1 405BLowest API billing cost

Speed / TokTok/Sec

Llama 3.1 405BFastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

Google: Gemma 4 26B A4B (free) (3)Llama 3.1 405B (0)

Google: Gemma 4 26B A4B (free)

3 of 3 Wins

✓Input price✓Output price✓Context window

Llama 3.1 405B

0 of 3 Wins

Competitive baseline across remaining benchmarks

Google

Leads 3 of 3

Google: Gemma 4 26B A4B (free)

Auto-discovered from OpenRouter (google/gemma-4-26b-a4b-it:free). Preview until a second source matches.

In: $0 · Out: $0/1M

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar LeaderGoogle: Gemma 4 26B A4B (free) Wins

Google: Gemma 4 26B A4B (free)

$0 / 1M output

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top standard models across 6 key capability dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect

0–100 %ile

Overall Matchup Breakdown

Category wins across reasoning intelligence, generation speed, and token cost.

Google: Gemma 4 26B A4B (free) (3)vsLlama 3.1 405B (7)

Google: Gemma 4 26B A4B (free): 3W (30%)Llama 3.1 405B: 7W (70%)

← Google: Gemma 4 26B A4B (free)Llama 3.1 405B →

🏆Llama 3.1 405B Leads(5/5)

Intelligence & Reasoning

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

Benchmark

Google: Gemma 4 26B A4B (free)vsLlama 3.1 405B

Preference Elo

—vs1,370

Coding Elo

—vs1,385

SWE-bench

—vs58.4%

LiveBench

—vs61.2%

GPQA Diamond

—vs75.2%

Google: Gemma 4 26B A4B (free): 0WLlama 3.1 405B: 5W

🏆Llama 3.1 405B Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark

Google: Gemma 4 26B A4B (free)vsLlama 3.1 405B

Output speed

—vs42 tok/s

Time to first token

—vs360 ms

Google: Gemma 4 26B A4B (free): 0WLlama 3.1 405B: 2W

🏆Google: Gemma 4 26B A4B (free) Leads(3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark

Google: Gemma 4 26B A4B (free)vsLlama 3.1 405B

Output price

$0/1Mvs$3.5/1M+$3.5/1M

Input price

$0/1Mvs$1.25/1M+$1.25/1M

Context window

262kvs128k+134k

Google: Gemma 4 26B A4B (free): 3WLlama 3.1 405B: 0W

Side-by-Side Benchmark Matrix

Google: Gemma 4 26B A4B (free)Llama 3.1 405B

Preference Elo

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B1,370

Coding Elo

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B1,385

LiveBench

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B61.2%

SWE-bench

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B58.4%

GPQA Diamond

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B75.2%

Time to first token

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B360 ms

Output speed

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B42 tok/s

Input priceGoogle: Gemma 4 26B A4B (free) +$1.25/1M

Google: Gemma 4 26B A4B (free)$0/1M

Llama 3.1 405B$1.25/1M

Output priceGoogle: Gemma 4 26B A4B (free) +$3.5/1M

Google: Gemma 4 26B A4B (free)$0/1M

Llama 3.1 405B$3.5/1M

Context windowGoogle: Gemma 4 26B A4B (free) +134k

Google: Gemma 4 26B A4B (free)262k

Llama 3.1 405B128k

Benchmark	Google: Gemma 4 26B A4B (free)	Llama 3.1 405B	Advantage Delta
Preference Elo	—	1,370 lmarena · Aug 17, 2026	—
Coding Elo	—	1,385 lmarena · Aug 17, 2026	—
LiveBench	—	61.2% livebench · Aug 17, 2026	—
SWE-bench	—	58.4% swebench · Aug 17, 2026	—
GPQA Diamond	—	75.2% seed-bootstrap · Aug 1, 2026	—
Time to first token	—	360 ms seed-bootstrap · Aug 1, 2026	—
Output speed	—	42 tok/s seed-bootstrap · Aug 1, 2026	—
Input price	$0/1M openrouter · Aug 17, 2026	$1.25/1M seed-bootstrap · Aug 1, 2026	+$1.25/1M
Output price	$0/1M openrouter · Aug 17, 2026	$3.5/1M seed-bootstrap · Aug 1, 2026	+$3.5/1M
Context window	262k openrouter · Aug 17, 2026	128k seed-bootstrap · Aug 1, 2026	+134k

Key Selection Recommendations

1
Google: Gemma 4 26B A4B (free):Pick Google: Gemma 4 26B A4B (free) when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGoogle: Gemma 4 26B A4B (free)

Lower output list price ($0/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGoogle: Gemma 4 26B A4B (free)

Larger window (262k).

Screenshots / visionLlama 3.1 405B

Llama 3.1 405B is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Google: Gemma 4 26B A4B (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Google: Gemma 4 26B A4B (free)	Larger window (262k).
Screenshots / vision	Llama 3.1 405B	Llama 3.1 405B is the side marked multimodal in the catalog.

Cast Your Matchup Vote

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

Google

Google: Gemma 4 26B A4B (free)

Elo n/a

SWE-bench—

Speed (tok/s)262k

Input / 1M Tokens$0/1M

Output / 1M Tokens$0/1M

Llama 3.1 405B

Elo 1,370

SWE-bench58.4%

Speed (tok/s)42 tok/s

Input / 1M Tokens$1.25/1M

Output / 1M Tokens$3.5/1M

Frequently Asked Questions

Which is better overall, Google: Gemma 4 26B A4B (free) or Llama 3.1 405B?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Google: Gemma 4 26B A4B (free) or Llama 3.1 405B?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: Google: Gemma 4 26B A4B (free) output tokens are $0/1M versus $3.5/1M. Input prices and retry rates still move the real bill.
Which is faster, Google: Gemma 4 26B A4B (free) or Llama 3.1 405B?: We do not have TTFT for both models.
Which has the larger context window?: Google: Gemma 4 26B A4B (free) accepts 262k 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. Google: Gemma 4 26B A4B (free) 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 Google: Gemma 4 26B A4B (free) matchups →|All Llama 3.1 405B matchups →

Llama 3.1 405B vs Llama 3.1 70B (next llama)Gemini 3 Pro vs Llama 3.1 405B Gemini 3 Flash vs Llama 3.1 405B Llama 4 Maverick vs Llama 3.1 405B Gemini 2.0 Flash Thinking vs Llama 3.1 405B Gemini 3.6 Pro vs Llama 3.1 405B

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top standard models across 6 key capability dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect

0–100 %ile

Side-by-Side Benchmark Matrix

Google: Gemma 4 26B A4B (free)Llama 3.1 405B

Preference Elo

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B1,370

Coding Elo

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B1,385

LiveBench

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B61.2%

SWE-bench

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B58.4%

GPQA Diamond

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B75.2%

Time to first token

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B360 ms

Output speed

Google: Gemma 4 26B A4B (free)—

Llama 3.1 405B42 tok/s

Input priceGoogle: Gemma 4 26B A4B (free) +$1.25/1M

Google: Gemma 4 26B A4B (free)$0/1M

Llama 3.1 405B$1.25/1M

Output priceGoogle: Gemma 4 26B A4B (free) +$3.5/1M

Google: Gemma 4 26B A4B (free)$0/1M

Llama 3.1 405B$3.5/1M

Context windowGoogle: Gemma 4 26B A4B (free) +134k

Google: Gemma 4 26B A4B (free)262k

Llama 3.1 405B128k

Benchmark

Google: Gemma 4 26B A4B (free)

Llama 3.1 405B

Advantage Delta

Preference Elo

—

1,370

lmarena · Aug 17, 2026

—

Coding Elo

—

1,385

lmarena · Aug 17, 2026

—

LiveBench

—

61.2%

livebench · Aug 17, 2026

—

SWE-bench

—

58.4%

swebench · Aug 17, 2026

—

GPQA Diamond

—

75.2%

seed-bootstrap · Aug 1, 2026

—

Time to first token

—

360 ms

seed-bootstrap · Aug 1, 2026

—

Output speed

—

42 tok/s

seed-bootstrap · Aug 1, 2026

—

Input price

$0/1M

openrouter · Aug 17, 2026

$1.25/1M

seed-bootstrap · Aug 1, 2026

+$1.25/1M

Output price

$0/1M

openrouter · Aug 17, 2026

$3.5/1M

seed-bootstrap · Aug 1, 2026

+$3.5/1M

Context window

262k

openrouter · Aug 17, 2026

128k

seed-bootstrap · Aug 1, 2026

+134k

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGoogle: Gemma 4 26B A4B (free)

Lower output list price ($0/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGoogle: Gemma 4 26B A4B (free)

Larger window (262k).

Screenshots / visionLlama 3.1 405B

Llama 3.1 405B is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Google: Gemma 4 26B A4B (free)	Lower output list price ($0/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Google: Gemma 4 26B A4B (free)	Larger window (262k).
Screenshots / vision	Llama 3.1 405B	Llama 3.1 405B is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Google: Gemma 4 26B A4B (free) or Llama 3.1 405B?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Google: Gemma 4 26B A4B (free) or Llama 3.1 405B?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

Google: Gemma 4 26B A4B (free) output tokens are $0/1M versus $3.5/1M. Input prices and retry rates still move the real bill.

Which is faster, Google: Gemma 4 26B A4B (free) or Llama 3.1 405B?

We do not have TTFT for both models.

Which has the larger context window?

Google: Gemma 4 26B A4B (free) accepts 262k 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. Google: Gemma 4 26B A4B (free) and Llama 3.1 405B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.