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Precision Benchmarks

Programmatic, dated AI model benchmarks, head-to-head comparisons, and Stack Engine presets.

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© 2026 CompareLLM. Public benchmark data aggregated from Arena Elo, LiveBench, SWE-bench & OpenRouter.

Every score has a dated snapshot.

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  2. Comparisons
  3. Google: Gemma 2 27B vs Kimi Chat 1.5

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

Google: Gemma 2 27B vs Kimi Chat 1.5 benchmark

In this head-to-head showdown, Google: Gemma 2 27B is more budget-friendly at $0.65/1M 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: Both Google: Gemma 2 27B and Kimi Chat 1.5 present distinct architectural strengths. Compare the verified benchmark matrix below to choose the model tailored to your specific application requirements.
Share Analysis:Share:
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Executive Verdict Summary

Kimi Chat 1.5 holds empirical advantage (2 of 3 metrics)

Coding / SWESWE-bench
Kimi Chat 1.5Top code solve rate
ReasoningGPQA / Live
Kimi Chat 1.5Top logical accuracy
Best Value$/1M Tok
Google: Gemma 2 27BLowest API billing cost
Speed / TokTok/Sec
Kimi Chat 1.5Fastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

Google: Gemma 2 27B (1)Kimi Chat 1.5 (2)
Google: Gemma 2 27B
1 of 3 Wins
✓Output price
Kimi Chat 1.5
2 of 3 Wins
✓Input price✓Context window
Google
Leads 1 of 3
Google: Gemma 2 27B

Auto-discovered from OpenRouter (google/gemma-2-27b-it). Preview until a second source matches.

In: $0.65 · Out: $0.65/1M
Moonshot
Leads 2 of 3
Kimi Chat 1.5

Moonshot ultra-long context model supporting up to 2 million tokens per request.

2M ContextElo 1,420In: $0.2 · Out: $0.8/1M
Top Rival Showdowns for Google: Gemma 2 27B
All Matchups
Compare vs:vs Claude Opus 4.5vs GPT-5vs Grok 4.6vs DeepSeek V4 Provs Qwen 3 Max
Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

Value per Dollar LeaderGoogle: Gemma 2 27B Wins

Google: Gemma 2 27B

$0.65 / 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 2 27B (1)vsKimi Chat 1.5 (9)
Google: Gemma 2 27B: 1W (10%)Overall: Kimi Chat 1.5Kimi Chat 1.5: 9W (90%)
← Google: Gemma 2 27BKimi Chat 1.5 →
🏆Kimi Chat 1.5 Leads(5/5)

Intelligence & Reasoning

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

Benchmark
Google: Gemma 2 27BvsKimi Chat 1.5
Preference Elo
—vs1,420
Coding Elo
—vs1,390
SWE-bench
—vs51%
LiveBench
—vs58%
GPQA Diamond
—vs71.5%
Google: Gemma 2 27B: 0WKimi Chat 1.5: 5W
🏆Kimi Chat 1.5 Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
Google: Gemma 2 27BvsKimi Chat 1.5
Output speed
—vs95 tok/s
Time to first token
—vs210 ms
Google: Gemma 2 27B: 0WKimi Chat 1.5: 2W
🏆Kimi Chat 1.5 Leads(2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark
Google: Gemma 2 27BvsKimi Chat 1.5
Output price
$0.65/1Mvs$0.8/1M+$0.15/1M
Input price
$0.65/1Mvs$0.2/1M+$0.45/1M
Context window
8kvs2M+2M
Google: Gemma 2 27B: 1WKimi Chat 1.5: 2W

Side-by-Side Benchmark Matrix

Google: Gemma 2 27BKimi Chat 1.5
Preference Elo
Google: Gemma 2 27B—
Kimi Chat 1.51,420
Coding Elo
Google: Gemma 2 27B—
Kimi Chat 1.51,390
LiveBench
Google: Gemma 2 27B—
Kimi Chat 1.558%
SWE-bench
Google: Gemma 2 27B—
Kimi Chat 1.551%
GPQA Diamond
Google: Gemma 2 27B—
Kimi Chat 1.571.5%
Time to first token
Google: Gemma 2 27B—
Kimi Chat 1.5210 ms
Output speed
Google: Gemma 2 27B—
Kimi Chat 1.595 tok/s
Input priceKimi Chat 1.5 +$0.45/1M
Google: Gemma 2 27B$0.65/1M
Kimi Chat 1.5$0.2/1M
Output priceGoogle: Gemma 2 27B +$0.15/1M
Google: Gemma 2 27B$0.65/1M
Kimi Chat 1.5$0.8/1M
Context windowKimi Chat 1.5 +2M
Google: Gemma 2 27B8k
Kimi Chat 1.52M
BenchmarkGoogle: Gemma 2 27BKimi Chat 1.5Advantage Delta
Preference Elo—
1,420
lmarena · Aug 17, 2026
—
Coding Elo—
1,390
lmarena · Aug 17, 2026
—
LiveBench—
58%
livebench · Aug 17, 2026
—
SWE-bench—
51%
swebench · Aug 17, 2026
—
GPQA Diamond—
71.5%
seed-bootstrap · Aug 1, 2026
—
Time to first token—
210 ms
seed-bootstrap · Aug 1, 2026
—
Output speed—
95 tok/s
seed-bootstrap · Aug 1, 2026
—
Input price
$0.65/1M
openrouter · Aug 17, 2026
$0.2/1M
seed-bootstrap · Aug 1, 2026
+$0.45/1M
Output price
$0.65/1M
openrouter · Aug 17, 2026
$0.8/1M
seed-bootstrap · Aug 1, 2026
+$0.15/1M
Context window
8k
openrouter · Aug 17, 2026
2M
seed-bootstrap · Aug 1, 2026
+2M

Workload Cost & Savings Calculator

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

Save 42% with Kimi Chat 1.5
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Google: Gemma 2 27B$32.50 / mo
In: $22.75Out: $9.75
Kimi Chat 1.5$19.00 / mo
In: $7Out: $12
Estimated Cost Delta

Kimi Chat 1.5 is estimated to save $13.50/month ($162/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    Google: Gemma 2 27B:Pick Google: Gemma 2 27B when you are optimizing output cost.
  • 2
    Kimi Chat 1.5:Pick Kimi Chat 1.5 for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGoogle: Gemma 2 27B

Lower output list price ($0.65/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGKimi Chat 1.5

Larger window (2M).

Screenshots / visionKimi Chat 1.5

Kimi Chat 1.5 is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatGoogle: Gemma 2 27BLower output list price ($0.65/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGKimi Chat 1.5Larger window (2M).
Screenshots / visionKimi Chat 1.5Kimi Chat 1.5 is the side marked multimodal in the catalog.

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK
VS
Google

Google: Gemma 2 27B

Elo n/a
SWE-bench—
Speed (tok/s)8k
Input / 1M Tokens$0.65/1M
Output / 1M Tokens$0.65/1M
Moonshot

Kimi Chat 1.5

Elo 1,420
SWE-bench51%
Speed (tok/s)95 tok/s
Input / 1M Tokens$0.2/1M
Output / 1M Tokens$0.8/1M

Frequently Asked Questions

Which is better overall, Google: Gemma 2 27B or Kimi Chat 1.5?
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 2 27B or Kimi Chat 1.5?
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 2 27B output tokens are $0.65/1M versus $0.8/1M. Input prices and retry rates still move the real bill.
Which is faster, Google: Gemma 2 27B or Kimi Chat 1.5?
We do not have TTFT for both models.
Which has the larger context window?
Kimi Chat 1.5 accepts 2M tokens versus 8k.
Can I self-host either model?
Neither model is marked open-weights here. You are comparing hosted APIs.
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 2 27B and Kimi Chat 1.5 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Google: Gemma 2 27B matchups →|All Kimi Chat 1.5 matchups →
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