GPT-5.6 Luna vs Grok 4.3
At a Glance
| Compare |  GPT-5.6 LunaOpenAI | Grok 4.3xAI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #31 of 4652.7 score · 3/3 sources · complete | #40 of 4616.6 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 11.1–44.4 |
| CostLower is better · Published-token output estimate | #6 of 44$0.026 per LiveBench case | #7 of 44$0.028 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | #4 of 3864.8 score · 3/3 sources · complete | #33 of 3846.0 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 43.3–59.9 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.20Openai ↗ · Sep 3, 2026 | $1.25Xai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | $1.20Openai ↗ · Sep 3, 2026 | $2.50Xai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 1,050K | 1,000K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 3, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | GPT-5.6 Luna | Grok 4.3 |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,429.89100% of row best · rating · gpt-5.6-luna-xhigh; 95% CI [1425.11549148, 1434.66063238]; votes 28547; rank 86 | 1,397.7398% of row best · rating · grok-4.3; 95% CI [1394.01930088, 1401.44639527]; votes 66801; rank 145 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,258.53100% of row best · rating · gpt-5.6-luna-xhigh; 95% CI [1250.17799393, 1266.87249678]; votes 7793; rank 48 | 1,229.4798% of row best · rating · grok-4.3; 95% CI [1223.17337452, 1235.75913440]; votes 22688; rank 67 |
| LiveBench2026-06-25 · overall · leader | 77.05100% of row best · percent · gpt-5.6-luna-max · 21,799 output tokens / case | 69.2790% of row best · percent · grok-4.3 · 11,184 output tokens / case |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 84.47100% of row best · points · GPT-5.6 Luna (ultra) · 17,605 output tokens / case | 74.9189% of row best · points · Grok 4.3 (high) · 5,154 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 3 benchmark winsOverall lead | 0 benchmark wins |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | GPT-5.6 Luna | Grok 4.3 |
|---|---|---|
| Developer | OpenAI | xAI |
| Family | Gpt 5 6 | Grok 4 |
| Model | GPT-5.6 Luna | Grok 4.3 |
| Version | GPT-5.6 Luna | Grok 4.3 |
| Lifecycle | active | active |
| Released | Unknown | 2026-06-17 |
| Knowledge cutoff | 2026-02-16 | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,050K | 1,000K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | Yes |
| Self-hostable | No | No |
| Provider access | Openai (Standard), Openrouter (Standard) | Xai (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, structured_outputs, tools |
GPT-5.6 Luna Capabilities
Grok 4.3 Capabilities
Related Comparisons
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|---|---|---|---|
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GPT-5.6 LunaOpenAI | vs | Grok 4.6xAI | cross-developer peersimage, text |
GPT-5.6 LunaOpenAI | vs |  Qwen3.8-MaxQwen | cross-developer peersimage, text |
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GPT-5.6 LunaOpenAI | vs |  GLM-5.3Z.ai | cross-developer peerstext |
GPT-5.6 LunaOpenAI | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | GPT-5.6 LunaOpenAI | cross-developer peersimage, text |
 Mistral Large 3Mistral AI | vs | GPT-5.6 LunaOpenAI | cross-developer peersimage, text |
Primary Evidence
Sources and Freshness
Questions
GPT-5.6 Luna vs Grok 4.3 FAQs
Is GPT-5.6 Luna or Grok 4.3 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both GPT-5.6 Luna and Grok 4.3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, GPT-5.6 Luna or Grok 4.3?+
GPT-5.6 Luna is $0.20 and Grok 4.3 is $1.25 per million tokens, so GPT-5.6 Luna is cheaper on this metric. GPT-5.6 Luna is $1.20 and Grok 4.3 is $2.50 per million tokens, so GPT-5.6 Luna is cheaper on this metric.
Which has a larger context window, GPT-5.6 Luna or Grok 4.3?+
GPT-5.6 Luna has the larger sourced context window. GPT-5.6 Luna supports 1,050K and Grok 4.3 supports 1,000K.
Which performs better in benchmarks, GPT-5.6 Luna or Grok 4.3?+
GPT-5.6 Luna leads the current overall benchmark count. The result uses 3 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can GPT-5.6 Luna or Grok 4.3 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. GPT-5.6 Luna is not marked open weight; Grok 4.3 is not marked open weight.
Can GPT-5.6 Luna and Grok 4.3 understand images?+
GPT-5.6 Luna is documented with image input; Grok 4.3 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, GPT-5.6 Luna or Grok 4.3?+
Neither has a larger sourced maximum output. GPT-5.6 Luna is 128K and Grok 4.3 is —.
Do GPT-5.6 Luna and Grok 4.3 support reasoning and tool use?+
GPT-5.6 Luna: reasoning, tool calling, and image input. Grok 4.3: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, GPT-5.6 Luna or Grok 4.3?+
GPT-5.6 Luna has 2 sourced provider routes; Grok 4.3 has 1, so GPT-5.6 Luna has broader tracked availability.
Which offers better value, GPT-5.6 Luna or Grok 4.3?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.