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  3. Llama 3.1 405B vs MiniMax: MiniMax M3 (batch)

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

Llama 3.1 405B vs MiniMax: MiniMax M3 (batch) benchmark

In this head-to-head showdown, MiniMax: MiniMax M3 (batch) is more budget-friendly at $0.6/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Executive Comparison Verdict

Bottom Line: Choose Llama 3.1 405B if your priority is peak reasoning, complex code generation, and top preference Elo. Choose MiniMax: MiniMax M3 (batch) if you are optimizing for low latency, high throughput, and cost-efficient API deployment.
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Executive Verdict Summary

MiniMax: MiniMax M3 (batch) 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
MiniMax: MiniMax M3 (batch)Lowest API billing cost
Speed / TokTok/Sec
Llama 3.1 405BFastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

Llama 3.1 405B (0)MiniMax: MiniMax M3 (batch) (3)
Llama 3.1 405B
0 of 3 Wins
Competitive baseline across remaining benchmarks
MiniMax: MiniMax M3 (batch)
3 of 3 Wins
✓Input price✓Output price✓Context window
Meta
Llama 3.1 405B

Meta flagship open-weight 405B dense foundation model with 128k context window.

Elo 1,370In: $1.25 · Out: $3.5/1M
MiniMax
Leads 3 of 3
MiniMax: MiniMax M3 (batch)

Auto-discovered from OpenRouter (minimax/minimax-m3:batch). Preview until a second source matches.

In: $0.15 · Out: $0.6/1M
Top Rival Showdowns for Llama 3.1 405B
All Matchups
Compare vs:vs Claude Opus 4.5vs GPT-5vs Gemini 3 Provs Grok 4.6vs DeepSeek V4 Pro
Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar LeaderMiniMax: MiniMax M3 (batch) Wins

MiniMax: MiniMax M3 (batch)

$0.6 / 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.

Llama 3.1 405B (7)vsMiniMax: MiniMax M3 (batch) (3)
Llama 3.1 405B: 7W (70%)Overall: Llama 3.1 405BMiniMax: MiniMax M3 (batch): 3W (30%)
← Llama 3.1 405BMiniMax: MiniMax M3 (batch) →
🏆Llama 3.1 405B Leads(5/5)

Intelligence & Reasoning

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

Benchmark
Llama 3.1 405BvsMiniMax: MiniMax M3 (batch)
Preference Elo
1,370vs—
Coding Elo
1,385vs—
SWE-bench
58.4%vs—
LiveBench
61.2%vs—
GPQA Diamond
75.2%vs—
Llama 3.1 405B: 5WMiniMax: MiniMax M3 (batch): 0W
🏆Llama 3.1 405B Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
Llama 3.1 405BvsMiniMax: MiniMax M3 (batch)
Output speed
42 tok/svs—
Time to first token
360 msvs—
Llama 3.1 405B: 2WMiniMax: MiniMax M3 (batch): 0W
🏆MiniMax: MiniMax M3 (batch) Leads(3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark
Llama 3.1 405BvsMiniMax: MiniMax M3 (batch)
Output price
$3.5/1Mvs$0.6/1M+$2.9/1M
Input price
$1.25/1Mvs$0.15/1M+$1.1/1M
Context window
128kvs524k+396k
Llama 3.1 405B: 0WMiniMax: MiniMax M3 (batch): 3W

Side-by-Side Benchmark Matrix

Llama 3.1 405BMiniMax: MiniMax M3 (batch)
Preference Elo
Llama 3.1 405B1,370
MiniMax: MiniMax M3 (batch)—
Coding Elo
Llama 3.1 405B1,385
MiniMax: MiniMax M3 (batch)—
LiveBench
Llama 3.1 405B61.2%
MiniMax: MiniMax M3 (batch)—
SWE-bench
Llama 3.1 405B58.4%
MiniMax: MiniMax M3 (batch)—
GPQA Diamond
Llama 3.1 405B75.2%
MiniMax: MiniMax M3 (batch)—
Time to first token
Llama 3.1 405B360 ms
MiniMax: MiniMax M3 (batch)—
Output speed
Llama 3.1 405B42 tok/s
MiniMax: MiniMax M3 (batch)—
Input priceMiniMax: MiniMax M3 (batch) +$1.1/1M
Llama 3.1 405B$1.25/1M
MiniMax: MiniMax M3 (batch)$0.15/1M
Output priceMiniMax: MiniMax M3 (batch) +$2.9/1M
Llama 3.1 405B$3.5/1M
MiniMax: MiniMax M3 (batch)$0.6/1M
Context windowMiniMax: MiniMax M3 (batch) +396k
Llama 3.1 405B128k
MiniMax: MiniMax M3 (batch)524k
BenchmarkLlama 3.1 405BMiniMax: MiniMax M3 (batch)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
$1.25/1M
seed-bootstrap · Aug 1, 2026
$0.15/1M
openrouter · Aug 17, 2026
+$1.1/1M
Output price
$3.5/1M
seed-bootstrap · Aug 1, 2026
$0.6/1M
openrouter · Aug 17, 2026
+$2.9/1M
Context window
128k
seed-bootstrap · Aug 1, 2026
524k
openrouter · Aug 17, 2026
+396k

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save 85% with MiniMax: MiniMax M3 (batch)
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Llama 3.1 405B$96.25 / mo
In: $43.75Out: $52.5
MiniMax: MiniMax M3 (batch)$14.25 / mo
In: $5.25Out: $9
Estimated Cost Delta

MiniMax: MiniMax M3 (batch) is estimated to save $82.00/month ($984/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    MiniMax: MiniMax M3 (batch):Pick MiniMax: MiniMax M3 (batch) when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatMiniMax: MiniMax M3 (batch)

Lower output list price ($0.6/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGMiniMax: MiniMax M3 (batch)

Larger window (524k).

Screenshots / visionMiniMax: MiniMax M3 (batch)

MiniMax: MiniMax M3 (batch) is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatMiniMax: MiniMax M3 (batch)Lower output list price ($0.6/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGMiniMax: MiniMax M3 (batch)Larger window (524k).
Screenshots / visionMiniMax: MiniMax M3 (batch)MiniMax: MiniMax M3 (batch) 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
VS
Meta

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
MiniMax

MiniMax: MiniMax M3 (batch)

Elo n/a
SWE-bench—
Speed (tok/s)524k
Input / 1M Tokens$0.15/1M
Output / 1M Tokens$0.6/1M

Frequently Asked Questions

Which is better overall, Llama 3.1 405B or MiniMax: MiniMax M3 (batch)?
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, Llama 3.1 405B or MiniMax: MiniMax M3 (batch)?
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?
MiniMax: MiniMax M3 (batch) output tokens are $0.6/1M versus $3.5/1M. Input prices and retry rates still move the real bill.
Which is faster, Llama 3.1 405B or MiniMax: MiniMax M3 (batch)?
We do not have TTFT for both models.
Which has the larger context window?
MiniMax: MiniMax M3 (batch) accepts 524k 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. Llama 3.1 405B and MiniMax: MiniMax M3 (batch) Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Llama 3.1 405B matchups →|All MiniMax: MiniMax M3 (batch) matchups →
Llama 3.1 405B vs Llama 3.1 70B (next llama)Llama 4 Maverick vs Llama 3.1 405BMiniMax M2.5 vs Llama 3.1 405BLlama 4 Scout vs Llama 3.1 405BLlama 3.3 70B vs Llama 3.1 405BMistral Large 3 vs Llama 3.1 405B