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  3. Kimi Chat 1.5 vs Qwen: Qwen3 30B A3B Instruct 2507

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

Kimi Chat 1.5 vs Qwen: Qwen3 30B A3B Instruct 2507 benchmark

In this head-to-head showdown, Qwen: Qwen3 30B A3B Instruct 2507 is more budget-friendly at $0.193/1M 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 Kimi Chat 1.5 if your priority is peak reasoning, complex code generation, and top preference Elo. Choose Qwen: Qwen3 30B A3B Instruct 2507 if you are optimizing for low latency, high throughput, and cost-efficient API deployment.
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Executive Verdict Summary

Qwen: Qwen3 30B A3B Instruct 2507 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
Qwen: Qwen3 30B A3B Instruct 2507Lowest API billing cost
Speed / TokTok/Sec
Kimi Chat 1.5Fastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

Kimi Chat 1.5 (1)Qwen: Qwen3 30B A3B Instruct 2507 (2)
Kimi Chat 1.5
1 of 3 Wins
✓Context window
Qwen: Qwen3 30B A3B Instruct 2507
2 of 3 Wins
✓Input price✓Output price
Moonshot
Leads 1 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
Alibaba
Leads 2 of 3
Qwen: Qwen3 30B A3B Instruct 2507

Auto-discovered from OpenRouter (qwen/qwen3-30b-a3b-instruct-2507). Preview until a second source matches.

In: $0.048 · Out: $0.193/1M

Kimi Series Lineage & Sibling Variants

4 models

Currently comparing Kimi Chat 1.5 vs Qwen: Qwen3 30B A3B Instruct 2507. Alternative family tiers available.

Active: Kimi Chat 1.5
Kimi K3$15MoonshotAI: Kimi K2.5$2.85MoonshotAI: Kimi K2 0711$2.3
Top Rival Showdowns for Kimi Chat 1.5
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 LeaderQwen: Qwen3 30B A3B Instruct 2507 Wins

Qwen: Qwen3 30B A3B Instruct 2507

$0.19305 / 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.

Kimi Chat 1.5 (8)vsQwen: Qwen3 30B A3B Instruct 2507 (2)
Kimi Chat 1.5: 8W (80%)Overall: Kimi Chat 1.5Qwen: Qwen3 30B A3B Instruct 2507: 2W (20%)
← Kimi Chat 1.5Qwen: Qwen3 30B A3B Instruct 2507 →
🏆Kimi Chat 1.5 Leads(5/5)

Intelligence & Reasoning

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

Benchmark
Kimi Chat 1.5vsQwen: Qwen3 30B A3B Instruct 2507
Preference Elo
1,420vs—
Coding Elo
1,390vs—
SWE-bench
51%vs—
LiveBench
58%vs—
GPQA Diamond
71.5%vs—
Kimi Chat 1.5: 5WQwen: Qwen3 30B A3B Instruct 2507: 0W
🏆Kimi Chat 1.5 Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
Kimi Chat 1.5vsQwen: Qwen3 30B A3B Instruct 2507
Output speed
95 tok/svs—
Time to first token
210 msvs—
Kimi Chat 1.5: 2WQwen: Qwen3 30B A3B Instruct 2507: 0W
🏆Qwen: Qwen3 30B A3B Instruct 2507 Leads(2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark
Kimi Chat 1.5vsQwen: Qwen3 30B A3B Instruct 2507
Output price
$0.8/1Mvs$0.193/1M+$0.607/1M
Input price
$0.2/1Mvs$0.048/1M+$0.152/1M
Context window
2Mvs262k+1.7M
Kimi Chat 1.5: 1WQwen: Qwen3 30B A3B Instruct 2507: 2W

Side-by-Side Benchmark Matrix

Kimi Chat 1.5Qwen: Qwen3 30B A3B Instruct 2507
Preference Elo
Kimi Chat 1.51,420
Qwen: Qwen3 30B A3B Instruct 2507—
Coding Elo
Kimi Chat 1.51,390
Qwen: Qwen3 30B A3B Instruct 2507—
LiveBench
Kimi Chat 1.558%
Qwen: Qwen3 30B A3B Instruct 2507—
SWE-bench
Kimi Chat 1.551%
Qwen: Qwen3 30B A3B Instruct 2507—
GPQA Diamond
Kimi Chat 1.571.5%
Qwen: Qwen3 30B A3B Instruct 2507—
Time to first token
Kimi Chat 1.5210 ms
Qwen: Qwen3 30B A3B Instruct 2507—
Output speed
Kimi Chat 1.595 tok/s
Qwen: Qwen3 30B A3B Instruct 2507—
Input priceQwen: Qwen3 30B A3B Instruct 2507 +$0.152/1M
Kimi Chat 1.5$0.2/1M
Qwen: Qwen3 30B A3B Instruct 2507$0.048/1M
Output priceQwen: Qwen3 30B A3B Instruct 2507 +$0.607/1M
Kimi Chat 1.5$0.8/1M
Qwen: Qwen3 30B A3B Instruct 2507$0.193/1M
Context windowKimi Chat 1.5 +1.7M
Kimi Chat 1.52M
Qwen: Qwen3 30B A3B Instruct 2507262k
BenchmarkKimi Chat 1.5Qwen: Qwen3 30B A3B Instruct 2507Advantage 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
$0.2/1M
seed-bootstrap · Aug 1, 2026
$0.048/1M
openrouter · Aug 17, 2026
+$0.152/1M
Output price
$0.8/1M
seed-bootstrap · Aug 1, 2026
$0.193/1M
openrouter · Aug 17, 2026
+$0.607/1M
Context window
2M
seed-bootstrap · Aug 1, 2026
262k
openrouter · Aug 17, 2026
+1.7M

Workload Cost & Savings Calculator

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

Save 76% with Qwen: Qwen3 30B A3B Instruct 2507
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Kimi Chat 1.5$19.00 / mo
In: $7Out: $12
Qwen: Qwen3 30B A3B Instruct 2507$4.58 / mo
In: $1.69Out: $2.9
Estimated Cost Delta

Qwen: Qwen3 30B A3B Instruct 2507 is estimated to save $14.42/month ($173/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    Qwen: Qwen3 30B A3B Instruct 2507:Pick Qwen: Qwen3 30B A3B Instruct 2507 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 chatQwen: Qwen3 30B A3B Instruct 2507

Lower output list price ($0.193/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGKimi Chat 1.5

Larger window (2M).

Screenshots / visionQwen: Qwen3 30B A3B Instruct 2507

Qwen: Qwen3 30B A3B Instruct 2507 is the side marked multimodal in the catalog.

Target WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsinsufficient dataNeed SWE-bench on both sides.
High-volume chatQwen: Qwen3 30B A3B Instruct 2507Lower output list price ($0.193/1M).
Voice / low-latency UIinsufficient dataNeed TTFT on both sides.
Long-document RAGKimi Chat 1.5Larger window (2M).
Screenshots / visionQwen: Qwen3 30B A3B Instruct 2507Qwen: Qwen3 30B A3B Instruct 2507 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
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
Alibaba

Qwen: Qwen3 30B A3B Instruct 2507

Elo n/a
SWE-bench—
Speed (tok/s)262k
Input / 1M Tokens$0.048/1M
Output / 1M Tokens$0.193/1M

Frequently Asked Questions

Which is better overall, Kimi Chat 1.5 or Qwen: Qwen3 30B A3B Instruct 2507?
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, Kimi Chat 1.5 or Qwen: Qwen3 30B A3B Instruct 2507?
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?
Qwen: Qwen3 30B A3B Instruct 2507 output tokens are $0.193/1M versus $0.8/1M. Input prices and retry rates still move the real bill.
Which is faster, Kimi Chat 1.5 or Qwen: Qwen3 30B A3B Instruct 2507?
We do not have TTFT for both models.
Which has the larger context window?
Kimi Chat 1.5 accepts 2M tokens versus 262k.
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. Kimi Chat 1.5 and Qwen: Qwen3 30B A3B Instruct 2507 Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Kimi Chat 1.5 matchups →|All Qwen: Qwen3 30B A3B Instruct 2507 matchups →
Kimi Chat 1.5 vs MoonshotAI: Kimi K2 0711 (next kimi)Qwen 3 Max vs Kimi Chat 1.5Kimi K3 vs Kimi Chat 1.5Qwen QwQ 32B vs Kimi Chat 1.5Qwen2.5 Coder 32B Instruct vs Kimi Chat 1.5Qwen 2.5 Plus vs Kimi Chat 1.5