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Qwen3.5-Flash vs GLM 4.5

Qwen3.5-Flash

Alibaba

68#113
vs
GLM 4.5

Zhipu AI

68#112
Signal-by-Signal Comparison
SignalQwen3.5-FlashDeltaGLM 4.5
Capabilities
83
+17
67
Benchmarks
66
-2
68
Pricing
100
+2
98
Context window size
86
+13
73
Recency
100
+32
68
Output Capacity
80
-3
83
Overall Result
4 wins
of 6
2 wins
Qwen3.5-Flash wins 4 of 6 signals

Score History

Score History (22 data points)
Qwen3.5-FlashGLM 4.5
Qwen3.5-Flash

68.2

current score

Leader

GLM 4.5

right now

GLM 4.5

68.3

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

Qwen3.5-Flash

Alibaba

Best Value
Per request$0.000195
Daily$0.65
Monthly$19.50
Annual$234.00

GLM 4.5

Zhipu AI

Per request$0.001700
Daily$5.67
Monthly$170.00
Annual$2040.00

Qwen3.5-Flash saves you $150.50/month

That's $1806.00/year compared to GLM 4.5 at your current usage level of 100K calls/month.

89% cheaper
Choose Qwen3.5-Flash for cost optimization

Qwen3.5-Flash pricing:
Input:$0.07/M tokens
Output:$0.26/M tokens
GLM 4.5 pricing:
Input:$0.60/M tokens
Output:$2.20/M tokens
Qwen3.5-Flash

Alibaba

68

Composite Score

Winner
GLM 4.5

Zhipu AI

68

Composite Score

Signal-by-Signal Comparison
MetricQwen3.5-FlashGLM 4.5Winner
Overall Score
68
68
GLM 4.5
Rank#113#112
GLM 4.5
Quality Rank#113#112
GLM 4.5
Adoption Rank#113#112
GLM 4.5
Parameters------
Context Window1000K131K
Qwen3.5-Flash
Pricing$0.07/$0.26/M$0.60/$2.20/M--
Signal Scores
Capabilities
83
67
Qwen3.5-Flash
Benchmarks
66
68
GLM 4.5
Pricing
100
98
Qwen3.5-Flash
Context window size
86
73
Qwen3.5-Flash
Recency
100
68
Qwen3.5-Flash
Output Capacity
80
83
GLM 4.5
Benchmark Head-to-Head(1 benchmarks)
Qwen3.5-Flash: 0GLM 4.5: 1
Qwen3.5-Flash
GLM 4.5
Normalized 0-100%
Arena Elo
13981411
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

Qwen3.5-FlashCompetitive

Scores 68/100 (rank #113), placing it in the top 61% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
GLM 4.5Competitive

Scores 68/100 (rank #112), placing it in the top 62% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose Qwen3.5-Flash when you need:

  • High-volume production workloads where API costs must be minimized
  • Processing long documents or large codebases (1000K token context)
  • Multimodal workflows that require image understanding
  • Step-by-step reasoning and chain-of-thought problem solving

Choose GLM 4.5 when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
Qwen3.5-FlashBest Value
Input cost$0.07/M tokens
Output cost$0.26/M tokens
Cost per quality point$0.005
Est. monthly (1M tokens/day)$4.88
GLM 4.5
Input cost$0.60/M tokens
Output cost$2.20/M tokens
Cost per quality point$0.041
Est. monthly (1M tokens/day)$42.00

Qwen3.5-Flash offers 88% better value per quality point. At 1M tokens/day, you'd spend $4.88/month with Qwen3.5-Flash vs $42.00/month with GLM 4.5 - a $37.13 monthly difference.

Latency & Speed
Qwen3.5-FlashFaster
Speed score0/100
GLM 4.5
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

Qwen3.5-Flash

Customer support chatbot

Suitable for user-facing chat with competitive response times. Qwen3.5-Flash also offers lower per-token costs for high-volume support

Qwen3.5-Flash

Long document analysis

Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass

Qwen3.5-Flash

Batch data extraction

Lower output pricing ($0.26/M) reduces costs when processing thousands of records daily

Qwen3.5-Flash

Creative writing & content

Higher overall composite score (68/100) correlates with better nuance, coherence, and style in long-form content

GLM 4.5

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

Qwen3.5-Flash
Which Should You Choose?
Our recommendation:
GLM 4.5

Qwen3.5-Flash and GLM 4.5 are extremely close in overall performance (only 0.09999999999999432 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

by Alibaba

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 88% lower pricing; better value at scale
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale
GLM 4.5
Recommended

by Zhipu AI

Consider for specialized use cases.

Capability Comparison
CapabilityQwen3.5-FlashGLM 4.5
Vision (Image Input)differs
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Qwen3.5-Flash

Alibaba

Best Value
$0.4290
estimated monthly cost

GLM 4.5

Zhipu AI

$3.72
estimated monthly cost

Qwen3.5-Flash saves you $3.29/month

That's 88% cheaper than GLM 4.5 at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterQwen3.5-FlashGLM 4.5
Context Window1M131K
Max Output Tokens65,53698,304
Open SourceNoYes
CreatedFeb 25, 2026Jul 25, 2025
Last updated: 28m ago

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