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Qwen3.5-35B-A3B vs GLM 5.3 (batch)

Qwen3.5-35B-A3B

Alibaba

69#142
vs
GLM 5.3 (batch)

Zhipu AI

69#140
Signal-by-Signal Comparison
SignalQwen3.5-35B-A3BDeltaGLM 5.3 (batch)
Capabilities
83
+17
67
Benchmarks
68
-1
69
Pricing
99
+1
98
Context window size
86
-9
96
Recency
91
-9
100
Output Capacity
67
-14
82
Overall Result
2 wins
of 6
4 wins
GLM 5.3 (batch) wins 4 of 6 signals

Score History

Score History (35 data points)
Qwen3.5-35B-A3BGLM 5.3 (batch)
Qwen3.5-35B-A3B

68.7

current score

Leader

GLM 5.3 (batch)

right now

GLM 5.3 (batch)

68.9

current score

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

Qwen3.5-35B-A3B

Alibaba

Best Value
Per request$0.000650
Daily$2.17
Monthly$65.00
Annual$780.00

GLM 5.3 (batch)

Zhipu AI

Per request$0.001450
Daily$4.83
Monthly$145.00
Annual$1740.00

Qwen3.5-35B-A3B saves you $80.00/month

That's $960.00/year compared to GLM 5.3 (batch) at your current usage level of 100K calls/month.

55% cheaper
Choose Qwen3.5-35B-A3B for cost optimization

Qwen3.5-35B-A3B pricing:
Input:$0.15/M tokens
Output:$1.00/M tokens
GLM 5.3 (batch) pricing:
Input:$0.45/M tokens
Output:$2.00/M tokens
Qwen3.5-35B-A3B

Alibaba

69

Composite Score

Winner
GLM 5.3 (batch)

Zhipu AI

69

Composite Score

Signal-by-Signal Comparison
MetricQwen3.5-35B-A3BGLM 5.3 (batch)Winner
Overall Score
69
69
GLM 5.3 (batch)
Rank#142#140
GLM 5.3 (batch)
Quality Rank#142#140
GLM 5.3 (batch)
Adoption Rank#142#140
GLM 5.3 (batch)
Parameters35B----
Context Window262K1049K
GLM 5.3 (batch)
Pricing$0.15/$1.00/M$0.45/$2.00/M--
Signal Scores
Capabilities
83
67
Qwen3.5-35B-A3B
Benchmarks
68
69
GLM 5.3 (batch)
Pricing
99
98
Qwen3.5-35B-A3B
Context window size
86
96
GLM 5.3 (batch)
Recency
91
100
GLM 5.3 (batch)
Output Capacity
67
82
GLM 5.3 (batch)
Benchmark Head-to-Head(1 benchmarks)
Qwen3.5-35B-A3B: 0GLM 5.3: 1
Qwen3.5-35B-A3B
GLM 5.3
Normalized 0-100%
MMLU-Pro
85.3%86%
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.

Qwen3.5-35B-A3BCompetitive

Scores 69/100 (rank #142), placing it in the top 51% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
GLM 5.3 (batch)Competitive

Scores 69/100 (rank #140), placing it in the top 52% 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 Qwen3.5-35B-A3B when you need:

  • High-volume production workloads where API costs must be minimized
  • Multimodal workflows that require image understanding
  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model

Choose GLM 5.3 (batch) when you need:

  • Processing long documents or large codebases (1049K token context)
  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model
Cost-Performance Analysis
Qwen3.5-35B-A3BBest Value
Input cost$0.15/M tokens
Output cost$1.00/M tokens
Cost per quality point$0.017
Est. monthly (1M tokens/day)$17.25
GLM 5.3 (batch)
Input cost$0.45/M tokens
Output cost$2.00/M tokens
Cost per quality point$0.036
Est. monthly (1M tokens/day)$36.75

Qwen3.5-35B-A3B offers 53% better value per quality point. At 1M tokens/day, you'd spend $17.25/month with Qwen3.5-35B-A3B vs $36.75/month with GLM 5.3 (batch) - a $19.50 monthly difference.

Latency & Speed
Qwen3.5-35B-A3BFaster
Speed score0/100
GLM 5.3 (batch)
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

Qwen3.5-35B-A3B

Customer support chatbot

Suitable for user-facing chat with competitive response times. Qwen3.5-35B-A3B also offers lower per-token costs for high-volume support

Qwen3.5-35B-A3B

Long document analysis

Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass

GLM 5.3 (batch)

Batch data extraction

Lower output pricing ($1.00/M) reduces costs when processing thousands of records daily

Qwen3.5-35B-A3B

Creative writing & content

Higher overall composite score (69/100) correlates with better nuance, coherence, and style in long-form content

GLM 5.3 (batch)

Image understanding & OCR

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

Qwen3.5-35B-A3B
Which Should You Choose?
Our recommendation:
GLM 5.3 (batch)

Qwen3.5-35B-A3B and GLM 5.3 (batch) are extremely close in overall performance (only 0.20000000000000284 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 - 53% 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 5.3 (batch)
Recommended

by Zhipu AI

Consider for specialized use cases.

Capability Comparison
CapabilityQwen3.5-35B-A3BGLM 5.3 (batch)
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)

Qwen3.5-35B-A3B

Alibaba

Best Value
$1.47
estimated monthly cost

GLM 5.3 (batch)

Zhipu AI

$3.21
estimated monthly cost

Qwen3.5-35B-A3B saves you $1.74/month

That's 54% cheaper than GLM 5.3 (batch) 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
ParameterQwen3.5-35B-A3BGLM 5.3 (batch)
Context Window262K1.0M
Max Output Tokens16,384131,072
Open SourceYesYes
CreatedFeb 25, 2026Aug 18, 2026
Last updated: 48m ago

相关对比

Qwen3.5-35B-A3B vs GLM 5.3 (batch) (2026) | LM Market Cap