text model comparison
GLM-5.3 vs Qwen3.8-Max
GLM-5.3 and Qwen3.8-Max are both current text models, from Z.ai and Alibaba Qwen. GLM-5.3 is 30% cheaper per 1M input tokens than Qwen3.8-Max, $1.40 vs $2. On Arena Text, GLM-5.3 scores 1481 Elo and Qwen3.8-Max 1482 Elo (Arena, measured October 28, 2026). Both accept 1,000,000 tokens of context.
- Higher Arena Text
- Qwen3.8-Max1482 Elo against 1481 Elo
- Lower price per 1M input tokens
- GLM-5.3$1.40 against $2
- Newer release
- GLM-5.3Aug 18, 2026 against Aug 2, 2026
Data verified November 3, 2026 · Dataset 2026-11-03
Side by side
GLM-5.3 and Qwen3.8-Max, line by line
Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.
| Fact | GLM-5.3 | Qwen3.8-Max |
|---|---|---|
| Price | ||
| Price per 1M input tokens | $1.40 (better) | $2 |
| Price per 1M output tokens | $4.40 (better) | $6 |
| Independent benchmarks | ||
| Arena Text | 1481 Elo (#16 of 51) | 1482 Elo (#13 of 51) (better) |
| Arena WebDev | 1623 Elo (#21 of 45) | 1672 Elo (#11 of 45) (better) |
| FrontierMath Tiers 1-3 (v2) | 68.8% (#25 of 42) | 74.7% (#20 of 42) (better) |
| GPQA Diamond | 90.9% (#23 of 41) | 92.7% (#18 of 41) (better) |
| SimpleQA Verified | 41% (#29 of 38) | 45.8% (#24 of 38) (better) |
| Specs | ||
| Provider | Z.ai | Alibaba Qwen |
| Release date | August 18, 2026 | August 2, 2026 |
| Access | API and open weights | API only |
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 128,000 tokens | 131,072 tokens |
| Input | text | text, image, video |
| Output | text | text |
Charts
Against every current text model
Where GLM-5.3 and Qwen3.8-Max land among the current models of their task, on every independent benchmark, on price and on context.
Where each stands
On Arena Text, GLM-5.3 ranks #16 and Qwen3.8-Max #13 of 51 current models. Each bar is the share of current models it beats: on score, price and context.
Independent benchmarks
Arena Text
GLM-5.3:#16of 51
1,481 Elo · ahead of 68%
Qwen3.8-Max:#13of 51
1,482 Elo · ahead of 72%
Arena WebDev
GLM-5.3:#21of 45
1,623 Elo · ahead of 55%
Qwen3.8-Max:#11of 45
1,672 Elo · ahead of 77%
FrontierMath Tiers 1-3 (v2)
GLM-5.3:#25of 42
68.8% · ahead of 41%
Qwen3.8-Max:#20of 42
74.7% · ahead of 54%
GPQA Diamond
GLM-5.3:#23of 41
90.9% · ahead of 45%
Qwen3.8-Max:#18of 41
92.7% · ahead of 55%
SimpleQA Verified
GLM-5.3:#29of 38
41% · ahead of 22%
Qwen3.8-Max:#24of 38
45.8% · ahead of 38%
Price and context
Price per 1M input tokens
GLM-5.3:#27of 52
$1.40 · cheaper than 49%
Qwen3.8-Max:#29of 52
$2 · cheaper than 24%
Price per 1M output tokens
GLM-5.3:#26of 52
$4.40 · cheaper than 51%
Qwen3.8-Max:#28of 52
$6 · cheaper than 41%
Context window
GLM-5.3:#26of 64
1M tokens · longer than 22%
Qwen3.8-Max:#26of 64
1M tokens · longer than 22%
Quality against price
GLM-5.3 scores 1,481 at $2.15; Qwen3.8-Max scores 1,482 at $3 (blended price per 1M tokens). The line joins the current models no other beats on both price and Arena Text score; hover any point to name it.
Quality against price: the data
| Model | Provider | Blended price per 1M tokens | Arena Text (Elo) |
|---|---|---|---|
| Gemini 4 Argon | $4 | 1,520 | |
| Claude Opus 5.5 | Anthropic | $8 | 1,509 |
| Muse Wonder | Meta | $8 | 1,507 |
| Claude Fable 5 | Anthropic | $20 | 1,504 |
| Claude Fable 5.1 | Anthropic | $20 | 1,504 |
| Gemini 3.8 Flash | $1.50 | 1,496 | |
| Muse Spark 1.3 | Meta | $2 | 1,495 |
| Claude Opus 5 | Anthropic | $10 | 1,492 |
| Kimi K3 | Moonshot Kimi | $6 | 1,488 |
| GPT-5.6 Sol | OpenAI | $8 | 1,485 |
| Gemini 3.6 Flash | $3 | 1,483 | |
| GPT-5.5 | OpenAI | $11 | 1,482 |
| Claude Opus 4.8 | Anthropic | $10 | 1,482 |
| Qwen3.8-Max | Alibaba Qwen | $3 | 1,482 |
| GPT-6.1 Sol | OpenAI | $4 | 1,481 |
| GLM-5.3 | Z.ai | $2.15 | 1,481 |
| MiMo-V2.6-Pro | Xiaomi MiMo | $0.54 | 1,480 |
| Claude Sonnet 5.5 | Anthropic | $4 | 1,477 |
| GLM-5.3-Flash | Z.ai | $0.24 | 1,477 |
| GPT-6 Astra | OpenAI | $20 | 1,476 |
| DeepSeek-V4.1-Flash | DeepSeek | $0.52 | 1,476 |
| GPT-5.4 | OpenAI | $5.63 | 1,475 |
| Gemini 3 Flash Preview | $1.13 | 1,473 | |
| Grok 4.20 | xAI | $1.56 | 1,472 |
| GPT-5.6 Terra | OpenAI | $4.50 | 1,467 |
| Grok 4.5 | xAI | $3 | 1,465 |
| DeepSeek-V4-Pro | DeepSeek | $1.98 | 1,465 |
| Claude Sonnet 5 | Anthropic | $4 | 1,462 |
| GPT-6 Sol | OpenAI | $4 | 1,458 |
| Gemini 3.5 Flash-Lite | $0.85 | 1,456 | |
| Grok 4.6 | xAI | $3 | 1,455 |
| GPT-5.6 Luna | OpenAI | $0.45 | 1,453 |
| MiMo-V2.6-Flash | Xiaomi MiMo | $0.18 | 1,448 |
| Step 5 Preview | StepFun | $1.43 | 1,448 |
| Grok 4.3 | xAI | $1.56 | 1,442 |
| GPT-6 Luna | OpenAI | $0.20 | 1,441 |
| Grok 4.7 | xAI | $3 | 1,441 |
| Mistral Large 4 | Mistral AI | $1.05 | 1,432 |
| Claude Haiku 5.5 | Anthropic | $0.20 | 1,425 |
| GPT-4.1 | OpenAI | $3.50 | 1,415 |
| Solar Pro 4 | Upstage | $0.52 | 1,388 |
| GPT-4.1 mini | OpenAI | $0.70 | 1,383 |
| GPT-4.1 nano | OpenAI | $0.18 | 1,322 |
Cost
What each costs
Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.
The same work, priced
For 10M input and 2M output tokens, Qwen3.8-Max costs 1.4 times as much as GLM-5.3, at each provider's listed rates.
10M input and 2M output tokens
Qwen3.8-Max costs 1.4× as much
- GLM-5.3
- $22.80
- Qwen3.8-Max
- $32
| Workload or rate | GLM-5.3 | Qwen3.8-Max |
|---|---|---|
| Example workloads | ||
| 10M input and 2M output tokens | $22.80 (better) | $32 |
| The same, with 9M of the input tokens cached | $12.54 | Not listed |
| Other listed rates | ||
| 1M input tokens, cached | $0.26 | Not listed |
Your own bill will differ. These figures use list prices and example workloads. The AI Model Cost Audit reviews your real usage, shortlists models that score as well for each task for less, and estimates the savings.
Launch price $100, regular price $150
Verdict
When to choose each
GLM-5.3
Where it leads
- Lower input and output prices, $1.40 and $4.40 vs $2 and $6 per 1M tokens
- Open weights you can run yourself
- A cached-input rate, $0.26 per 1M tokens
Best for
- Long-horizon agentic coding
- Self-hosted reasoning with permissive weights
Watch out for
- Text input only, and reasoning cannot be turned off: requests that disable thinking fail
- The licence requires a Z.ai security review before very large model-as-a-service operators use it commercially
Qwen3.8-Max
Where it leads
- Higher Arena Text score, 1482 Elo vs 1481 Elo
- Higher Arena WebDev score, 1672 Elo vs 1623 Elo
- Higher FrontierMath Tiers 1-3 (v2) score, 74.7% vs 68.8%
- Higher GPQA Diamond score, 92.7% vs 90.9%
- Higher SimpleQA Verified score, 45.8% vs 41%
- Accepts image and video input
Best for
- Output-heavy generation workloads where the $6 per million output rate is the deciding factor
- Agentic and coding evaluations that need a 1M-token window at mid-tier cost
Watch out for
- Two releases share the name: the original 2 August 2026 model and the 0902 refresh, a separate id at the same price
- The recorded rates are the international (Singapore) price; the Global and Beijing listings charge $1.65 input and $4.951 output per 1M tokens
- Alibaba publishes no fixed cached-input rate for it
From benchmark to production
Building on GLM-5.3 or Qwen3.8-Max?
Public scores rarely hold on your own data. We test both models on your real tasks, then build the agent or pipeline around the one that wins.
AI Model Cost AuditLaunch price $100, regular price $150What the audit includes
FAQ
GLM-5.3 vs Qwen3.8-Max FAQ
Which is cheaper, GLM-5.3 or Qwen3.8-Max?
GLM-5.3 is 30% cheaper per 1M input tokens than Qwen3.8-Max, $1.40 vs $2. For 10M input and 2M output tokens, GLM-5.3 costs $22.80 and Qwen3.8-Max $32 at standard rates.
Do GLM-5.3 and Qwen3.8-Max discount cached input?
GLM-5.3 lists a cached-input rate of $0.26 per 1M tokens, 81% below its standard input rate. No cached-input rate is listed for Qwen3.8-Max.
Which scores higher on independent benchmarks, GLM-5.3 or Qwen3.8-Max?
Qwen3.8-Max leads on Arena Text, 1482 Elo to 1481 Elo; Qwen3.8-Max leads on Arena WebDev, 1672 Elo to 1623 Elo; Qwen3.8-Max leads on FrontierMath Tiers 1-3 (v2), 74.7% to 68.8%. Scores are independent evaluations, not either vendor's launch figures.
Which has the larger context window, GLM-5.3 or Qwen3.8-Max?
Both accept 1,000,000 tokens of context. Qwen3.8-Max returns up to 131,072 tokens per response, GLM-5.3 128,000.
How do GLM-5.3 and Qwen3.8-Max differ in features?
GLM-5.3 takes text input; Qwen3.8-Max takes text, image and video.
Can I run GLM-5.3 or Qwen3.8-Max myself?
GLM-5.3 is released as open weights you can run yourself; Qwen3.8-Max is available through its provider's API only.
Further reading
More on GLM-5.3 and Qwen3.8-Max
Related comparisons
- GLM-5.3 vs Mistral Large 4
- Gemini 4 Argon vs Qwen3.8-Max
- Claude Opus 5.5 vs GLM-5.3
- Claude Sonnet 5.5 vs Qwen3.8-Max
- DeepSeek-V4.1-Flash vs GLM-5.3
- GPT-6 Luna vs Qwen3.8-Max
- Gemini 3.8 Flash vs GLM-5.3
- DeepSeek-V4.1-Flash vs Qwen3.8-Max
- DeepSeek-V4-Pro vs GLM-5.3
- Gemini 3.8 Flash vs Qwen3.8-Max
- Gemini 3.6 Flash vs GLM-5.3
- DeepSeek-V4-Pro vs Qwen3.8-Max
Production evaluation
Choosing between GLM-5.3 and Qwen3.8-Max?
Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- A head-to-head evaluation on your real workload
- Routing between models by cost and difficulty
