text model comparison
GLM-5.3 vs Inkling 2 Small
GLM-5.3 and Inkling 2 Small are both current text models, from Z.ai and Thinking Machines Lab. Inkling 2 Small is 79% cheaper per 1M input tokens than GLM-5.3, $0.30 vs $1.40. In Thinking Machines Lab's Inkling 2 Small model card, GLM-5.3 scores 69.0% on DeepSWE v1.1 and Inkling 2 Small 72.1%. GLM-5.3 has the larger context window, 1,000,000 vs 262,144 tokens.
- Lower price per 1M input tokens
- Inkling 2 Small$0.30 against $1.40
- Longer context window
- GLM-5.31M tokens against 262K tokens
- Newer release
- Inkling 2 SmallNov 2026 against Aug 2026
Data verified November 6, 2026 · Dataset 2026-11-06
Side by side
GLM-5.3 and Inkling 2 Small, 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 | Inkling 2 Small |
|---|---|---|
| Price | ||
| Price per 1M input tokens | $1.40 | $0.30 (better) |
| Price per 1M output tokens | $4.40 | $1 (better) |
| Independent benchmarks | ||
| Arena Text | 1481 Elo (#17 of 52) | Not measured |
| Arena WebDev | 1623 Elo (#22 of 46) | Not measured |
| GPQA Diamond | 90.9% (#23 of 41) | Not measured |
| FrontierMath Tiers 1-3 (v2) | 68.8% (#25 of 41) | Not measured |
| SimpleQA Verified | 41% (#29 of 38) | Not measured |
| Specs | ||
| Provider | Z.ai | Thinking Machines Lab |
| Release date | August 18, 2026 | November 5, 2026 |
| Access | API and open weights | API only |
| Context window | 1,000,000 tokens | 262,144 tokens |
| Max output | 128,000 tokens | Not reported |
| Input | text | text, image |
| Output | text | text |
No independent benchmark has scored both models yet. Each rank counts the current models scored on that benchmark.
Provider results
What the labs report
Results tables a lab published with one of its models, where it lists both GLM-5.3 and Inkling 2 Small. These are the lab's own figures, not independent measurements, and each table is read on its own: labs run benchmarks with different harnesses and budgets.
Thinking Machines Lab, Inkling 2 Small model card, November 5, 2026Thinking Machines Lab · 2026-11-06
| Benchmark | GLM-5.3 | Inkling 2 Small |
|---|---|---|
| DeepSWE v1.1 | 69.0% | 72.1% (better) |
| Vibe Code Bench v1.1 | 78.1% | 81.6% (better) |
| Sudo L7 | 15.0% (better) | 14.1% |
| SWE-Marathon v1.1 | 42.5% (better) | 38.8% |
| SWE-bench Multilingual | 87.6% (better) | 81.2% |
| SWE-bench Pro v2hard set | 84.3% | 86.3% (better) |
| SWE-bench Pro v2full set | 95.6% | 97.7% (better) |
| SWE-bench Verified | 95.4% (better) | 82.2% |
| PostTrainBench v1.2 | 34.5% (better) | 31.9% |
| MCP Atlasfull set | 84.2% | 85.4% (better) |
| MCP Atlaspublic set | 83.6% | 85.0% (better) |
| EnterpriseBench-CoreCraft | 51.8% | 71.8% (better) |
| Finance Agent v2.1 | 65.0% | 67.5% (better) |
| Excel Modeling Benchmark v1.1 | 69.1% | 69.5% (better) |
| Tax Agent Bench | 73.1% (better) | 65.8% |
| APEX-Accounting v1.1pass@1 | 13.9% | 14.5% (better) |
| APEX-Accounting v1.1mean score | 59.5% | 62.0% (better) |
| Diligence Benchbest harness | 49.4% | 58.1% (better) |
| Harvey LAB v1.1 | 14.6% | 21.7% (better) |
| Legal Research Bench | 49.0% (better) | 46.6% |
| GPQA-Diamond | 91.7% | 93.0% (better) |
| LongBench v2 | 68.4% | 70.6% (better) |
| ComplexConstraints v1.0 | 30.5% | 44.5% (better) |
| CyberBench v1.1 | 72.1% | 72.7% (better) |
| PatchEval | 69.6% | 79.6% (better) |
Thinking Machines' table from the Inkling 2 Small model card, run at effort 0.99 (xhigh) with a 1M-token trajectory limit; where a benchmark's owner publishes scores (Datacurve, Scale AI, Surge, Mercor, Thoughtful, Vals), Thinking Machines uses them. DeepSeek-V4.1-Flash is the 1017 build. Left out here: the Artificial Analysis and Vals indexes, the rows Artificial Analysis ran (FrontierCode, Terminal-Bench, GDP.pdf, MMMU-Pro, HLE, CritPt, AA-LCR, AA-Omniscience, AutomationBench, EnterpriseOps-Gym, Tau 3 Banking), Arena and DesignArena ratings, PMPP-Hard (not a percentage), the safety rows, and JobBench, DAYJOB and Humanity's Sixth Sense, which we could not confirm are public.
Charts
Against every current text model
Where GLM-5.3 and Inkling 2 Small land among the current models of their task, on every independent benchmark, on price and on context.
Where each stands
Only GLM-5.3 has a current Arena Text score: #17 of 52. Each bar is the share of current models it beats.
Independent benchmarks
Arena Text
GLM-5.3:#17of 52
1,481 Elo · ahead of 67%
Inkling 2 Small: Not scored
Arena WebDev
GLM-5.3:#22of 46
1,623 Elo · ahead of 53%
Inkling 2 Small: Not scored
GPQA Diamond
GLM-5.3:#23of 41
90.9% · ahead of 45%
Inkling 2 Small: Not scored
FrontierMath Tiers 1-3 (v2)
GLM-5.3:#25of 41
68.8% · ahead of 40%
Inkling 2 Small: Not scored
SimpleQA Verified
GLM-5.3:#29of 38
41% · ahead of 22%
Inkling 2 Small: Not scored
Price and context
Price per 1M input tokens
GLM-5.3:#29of 58
$1.40 · cheaper than 51%
Inkling 2 Small:#11of 58
$0.30 · cheaper than 75%
Price per 1M output tokens
GLM-5.3:#28of 58
$4.40 · cheaper than 53%
Inkling 2 Small:#10of 58
$1 · cheaper than 84%
Context window
GLM-5.3:#27of 67
1M tokens · longer than 24%
Inkling 2 Small:#57of 67
262K tokens · longer than 12%
Quality against price
GLM-5.3 scores 1,481 at $2.15 (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 Carbon | $4 | 1,528 | |
| 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, GLM-5.3 costs 4.6 times as much as Inkling 2 Small, at each provider's listed rates.
10M input and 2M output tokens
GLM-5.3 costs 4.6× as much
- GLM-5.3
- $22.80
- Inkling 2 Small
- $5
The same, with 9M of the input tokens cached
GLM-5.3 costs 4.9× as much
- GLM-5.3
- $12.54
- Inkling 2 Small
- $2.57
| Workload or rate | GLM-5.3 | Inkling 2 Small |
|---|---|---|
| Example workloads | ||
| 10M input and 2M output tokens | $22.80 | $5 (better) |
| The same, with 9M of the input tokens cached | $12.54 | $2.57 (better) |
| Other listed rates | ||
| 1M input tokens, cached | $0.26 | $0.03 (better) |
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
- Larger context window 1,000,000 vs 262,144 tokens
- Open weights you can run yourself
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
Inkling 2 Small
Where it leads
- Lower input and output prices, $0.30 and $1 vs $1.40 and $4.40 per 1M tokens
- Accepts image input
- Cheaper cached input, $0.03 vs $0.26 per 1M tokens
Best for
- Agentic coding and office, finance and legal work at a low per-token price
- Teams that want to post-train their own variant on Tinker
Watch out for
- Closed weights for now: Thinking Machines says it will publish the full weights under Apache 2.0 the week after launch, once external safety testing ends; until then Tinker is the only way to use it
- Tinker serves it with a 64K or 256K context, although the model card lists up to 1M tokens
- In its lab's own table DeepSeek-V4.1-Flash scores higher on DeepSWE v1.1 (77.0% against 72.1%) and Claude Haiku 5.5 on Vibe Code Bench (90.4% against 81.6%); Thinking Machines also says it is less tuned for chat, and no independent benchmark score is recorded here yet
From benchmark to production
Building on GLM-5.3 or Inkling 2 Small?
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 Inkling 2 Small FAQ
Which is cheaper, GLM-5.3 or Inkling 2 Small?
Inkling 2 Small is 79% cheaper per 1M input tokens than GLM-5.3, $0.30 vs $1.40. For 10M input and 2M output tokens, GLM-5.3 costs $22.80 and Inkling 2 Small $5 at standard rates.
Which is cheaper with prompt caching, GLM-5.3 or Inkling 2 Small?
GLM-5.3 charges $0.26 per 1M cached input tokens, 81% below its standard input rate, and Inkling 2 Small $0.03, 90% below. With 9M of 10M input tokens cached and 2M output tokens, GLM-5.3 costs $12.54 and Inkling 2 Small $2.57.
How do GLM-5.3 and Inkling 2 Small compare in Thinking Machines Lab's own results?
In the Inkling 2 Small model card (November 5, 2026), Inkling 2 Small leads on DeepSWE v1.1, 72.1% to 69.0%; Inkling 2 Small leads on Vibe Code Bench v1.1, 81.6% to 78.1%; GLM-5.3 leads on Sudo L7, 15.0% to 14.1%. These are Thinking Machines Lab's figures, not independent measurements.
Which has the larger context window, GLM-5.3 or Inkling 2 Small?
GLM-5.3 has the larger context window, 1,000,000 vs 262,144 tokens.
How do GLM-5.3 and Inkling 2 Small differ in features?
GLM-5.3 takes text input; Inkling 2 Small takes text and image.
Can I run GLM-5.3 or Inkling 2 Small myself?
GLM-5.3 is released as open weights you can run yourself; Inkling 2 Small is available through its provider's API only.
Further reading
More on GLM-5.3 and Inkling 2 Small
Related comparisons
- Claude Opus 5.5 vs GLM-5.3
- Claude Haiku 5.5 vs Inkling 2 Small
- DeepSeek-V4.1-Flash vs GLM-5.3
- DeepSeek-V4.1-Flash vs Inkling 2 Small
- Gemini 3.8 Flash vs GLM-5.3
- Gemini 3.5 Flash-Lite vs Inkling 2 Small
- DeepSeek-V4-Pro vs GLM-5.3
- Gemini 3.8 Flash vs Inkling 2 Small
- Gemini 3.6 Flash vs GLM-5.3
- GLM-5.3-Flash vs Inkling 2 Small
- GLM-5.3 vs Grok 4.20
- GPT-6 Luna vs Inkling 2 Small
Production evaluation
Choosing between GLM-5.3 and Inkling 2 Small?
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