text model comparison
GPT-6 Luna vs Inkling 2 Small
GPT-6 Luna and Inkling 2 Small are both current text models, from OpenAI and Thinking Machines Lab. GPT-6 Luna is 67% cheaper per 1M input tokens than Inkling 2 Small, $0.10 vs $0.30. In Thinking Machines Lab's Inkling 2 Small model card, GPT-6 Luna scores 66.6% on DeepSWE v1.1 and Inkling 2 Small 72.1%. GPT-6 Luna has the larger context window, 1,050,000 vs 262,144 tokens.
- Lower price per 1M input tokens
- GPT-6 Luna$0.10 against $0.30
- Longer context window
- GPT-6 Luna1.05M tokens against 262K tokens
- Newer release
- Inkling 2 SmallNov 2026 against Sep 2026
Data verified November 6, 2026 · Dataset 2026-11-06
Side by side
GPT-6 Luna 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 | GPT-6 Luna | Inkling 2 Small |
|---|---|---|
| Price | ||
| Price per 1M input tokens | $0.10 (better) | $0.30 |
| Price per 1M output tokens | $0.50 (better) | $1 |
| Independent benchmarks | ||
| Arena Text | 1441 Elo (#38 of 52) | Not measured |
| Arena WebDev | 1579 Elo (#29 of 46) | Not measured |
| GPQA Diamond | 90.5% (#26 of 41) | Not measured |
| FrontierMath Tiers 1-3 (v2) | 78.9% (#17 of 41) | Not measured |
| SimpleQA Verified | 41.4% (#28 of 38) | Not measured |
| Specs | ||
| Provider | OpenAI | Thinking Machines Lab |
| Release date | September 22, 2026 | November 5, 2026 |
| Access | API only | API only |
| Context window | 1,050,000 tokens | 262,144 tokens |
| Max output | 128,000 tokens | Not reported |
| Input | text, image | 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 GPT-6 Luna 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 | GPT-6 Luna | Inkling 2 Small |
|---|---|---|
| DeepSWE v1.1 | 66.6% | 72.1% (better) |
| Vibe Code Bench v1.1 | 81.7% (better) | 81.6% |
| SWE-Marathon v1.1 | 28.1% | 38.8% (better) |
| SWE-bench Multilingual | 78.2% | 81.2% (better) |
| SWE-bench Multimodal v2 | 37.5% | 43.1% (better) |
| SWE-bench Verified | 76.1% | 82.2% (better) |
| BioMysteryBench | 61.5% | 70.0% (better) |
| MCP Atlaspublic set | 77.8% | 85.0% (better) |
| Finance Agent v2.1 | 56.8% | 67.5% (better) |
| Excel Modeling Benchmark v1.1 | 70.0% (better) | 69.5% |
| Tax Agent Bench | 58.9% | 65.8% (better) |
| APEX-Accounting v1.1pass@1 | 10.8% | 14.5% (better) |
| APEX-Accounting v1.1mean score | 53.9% | 62.0% (better) |
| Diligence Benchbest harness | 42.1% | 58.1% (better) |
| Harvey LAB v1.1 | 4.2% | 21.7% (better) |
| Legal Research Bench | 30.3% | 46.6% (better) |
| PerceptionBench | 56.2% | 64.7% (better) |
| ScreenSpot-Pro | 81.1% | 83.8% (better) |
| ScreenSpot-Prowith Python | 87.6% | 91.5% (better) |
| CharXiv (RQ) | 81.8% | 85.6% (better) |
| CharXiv (RQ)with Python | 85.3% | 87.7% (better) |
| Chartography | 32.0% | 36.7% (better) |
| SAGE v1.1 | 83.4% | 88.6% (better) |
| LongBench v2 | 65.0% | 70.6% (better) |
| ComplexConstraints v1.0 | 27.3% | 44.5% (better) |
| CyberBench v1.1 | 76.3% (better) | 72.7% |
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 GPT-6 Luna 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 GPT-6 Luna has a current Arena Text score: #38 of 52. Each bar is the share of current models it beats.
Independent benchmarks
Arena Text
GPT-6 Luna:#38of 52
1,441 Elo · ahead of 25%
Inkling 2 Small: Not scored
Arena WebDev
GPT-6 Luna:#29of 46
1,579 Elo · ahead of 38%
Inkling 2 Small: Not scored
GPQA Diamond
GPT-6 Luna:#26of 41
90.5% · ahead of 35%
Inkling 2 Small: Not scored
FrontierMath Tiers 1-3 (v2)
GPT-6 Luna:#17of 41
78.9% · ahead of 60%
Inkling 2 Small: Not scored
SimpleQA Verified
GPT-6 Luna:#28of 38
41.4% · ahead of 27%
Inkling 2 Small: Not scored
Price and context
Price per 1M input tokens
GPT-6 Luna:#1of 58
$0.10 · cheaper than 96%
Inkling 2 Small:#11of 58
$0.30 · cheaper than 75%
Price per 1M output tokens
GPT-6 Luna:#3of 58
$0.50 · cheaper than 93%
Inkling 2 Small:#10of 58
$1 · cheaper than 84%
Context window
GPT-6 Luna:#1of 67
1.05M tokens · longer than 85%
Inkling 2 Small:#57of 67
262K tokens · longer than 12%
Quality against price
GPT-6 Luna scores 1,441 at $0.2 (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, Inkling 2 Small costs 2.5 times as much as GPT-6 Luna, at each provider's listed rates.
10M input and 2M output tokens
Inkling 2 Small costs 2.5× as much
- GPT-6 Luna
- $2
- Inkling 2 Small
- $5
The same, with 9M of the input tokens cached
Inkling 2 Small costs 2.2× as much
- GPT-6 Luna
- $1.19
- Inkling 2 Small
- $2.57
| Workload or rate | GPT-6 Luna | Inkling 2 Small |
|---|---|---|
| Example workloads | ||
| 10M input and 2M output tokens | $2 (better) | $5 |
| The same, with 9M of the input tokens cached | $1.19 (better) | $2.57 |
| Other listed rates | ||
| 1M input tokens, cached | $0.01 (better) | $0.03 |
| 1M input tokens, prompts over 272K tokens | $0.20 | Not listed |
| 1M output tokens, prompts over 272K tokens | $0.75 | 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
GPT-6 Luna
Where it leads
- Lower input and output prices, $0.10 and $0.50 vs $0.30 and $1 per 1M tokens
- Larger context window 1,050,000 vs 262,144 tokens
- Cheaper cached input, $0.01 vs $0.03 per 1M tokens
Best for
- High-volume summarisation, extraction and routing
- Long-context budget work, where the 272k threshold is more forgiving than Haiku 5.5's 100k
Watch out for
- Prompts over 272,000 tokens are rebilled at $0.20 input and $0.75 output for the whole request
- A twentieth of GPT-6 Sol's price reflects a capability gap, not a discount on the same model
Inkling 2 Small
Where it leads
No measured lead over GPT-6 Luna in this data.
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 GPT-6 Luna 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
GPT-6 Luna vs Inkling 2 Small FAQ
Which is cheaper, GPT-6 Luna or Inkling 2 Small?
GPT-6 Luna is 67% cheaper per 1M input tokens than Inkling 2 Small, $0.10 vs $0.30. For 10M input and 2M output tokens, GPT-6 Luna costs $2 and Inkling 2 Small $5 at standard rates.
Which is cheaper with prompt caching, GPT-6 Luna or Inkling 2 Small?
GPT-6 Luna charges $0.01 per 1M cached input tokens, 90% below its standard input rate, and Inkling 2 Small $0.03, 90% below. With 9M of 10M input tokens cached and 2M output tokens, GPT-6 Luna costs $1.19 and Inkling 2 Small $2.57.
How do GPT-6 Luna 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 66.6%; GPT-6 Luna leads on Vibe Code Bench v1.1, 81.7% to 81.6%; Inkling 2 Small leads on SWE-Marathon v1.1, 38.8% to 28.1%. These are Thinking Machines Lab's figures, not independent measurements.
Which has the larger context window, GPT-6 Luna or Inkling 2 Small?
GPT-6 Luna has the larger context window, 1,050,000 vs 262,144 tokens.
Further reading
More on GPT-6 Luna and Inkling 2 Small
Articles on GPT-6 Luna and Inkling 2 Small
- OpenAI Models on Google Cloud: What Changes for AI TeamsOctober 22, 2026
- Claude Sonnet 5.5 vs GPT-6 Luna: Cost, Speed and AccuracySeptember 29, 2026
- GPT-6 Sol vs Claude Opus 5.5, Plus Luna: Best Value per TaskSeptember 24, 2026
- GPT-6 Sol and Luna: Half the Price, and Where Each One FitsSeptember 23, 2026
Related comparisons
- Claude Haiku 5.5 vs GPT-6 Luna
- Claude Haiku 5.5 vs Inkling 2 Small
- GPT-6.1 Sol vs GPT-6 Luna
- DeepSeek-V4.1-Flash vs Inkling 2 Small
- Claude Sonnet 5.5 vs GPT-6 Luna
- Gemini 3.5 Flash-Lite vs Inkling 2 Small
- Claude Opus 5.5 vs GPT-6 Luna
- Gemini 3.8 Flash vs Inkling 2 Small
- DeepSeek-V4.1-Flash vs GPT-6 Luna
- GLM-5.3-Flash vs Inkling 2 Small
- GPT-5.4 vs GPT-6 Luna
- GLM-5.3 vs Inkling 2 Small
Production evaluation
Choosing between GPT-6 Luna 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