Mistral Medium 3.5 128B vs GPT-5.6 Luna
At a Glance
| Compare |  Mistral Medium 3.5 128BMistral AI |  GPT-5.6 LunaOpenAI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #31 of 4652.7 score · 3/3 sources · complete |
| CostLower is better · Published-token output estimate | UnrankedNot in the 44-model eligible cohort | #6 of 44$0.026 per LiveBench case |
| EfficiencyHigher is better · MM Efficiency v1.5 | UnrankedNot in the 38-model eligible cohort | #4 of 3864.8 score · 3/3 sources · complete |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $0.20Openai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $1.20Openai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 262K | 1,050K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 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 | Mistral-Medium-3.5-128B | GPT-5.6 Luna |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader | -10.8890% of row best · score · Mistral Medium 3.5; 95% CI [-12.33636331, -9.41760729]; sessions 10244; observations 358935; rank 43 | -0.44100% of row best · score · GPT 5.6 Luna (xHigh); 95% CI [-1.27310649, 0.39719069]; sessions 29186; observations 2307801; rank 27 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · statistical tie | 1,420.5899% of row best · rating · mistral-medium-3.5; 95% CI [1414.04225396, 1427.11615611]; votes 10996; rank 104 | 1,429.89100% of row best · rating · gpt-5.6-luna-xhigh; 95% CI [1425.11549148, 1434.66063238]; votes 28547; rank 86 |
| LMArena Vision Arenavision-2026-09-13-d25aabda0010 · arena_rating · leader | 1,222.0597% of row best · rating · mistral-medium-3.5; 95% CI [1212.30064904, 1231.79518832]; votes 5090; rank 71 | 1,258.53100% of row best · rating · gpt-5.6-luna-xhigh; 95% CI [1250.17799393, 1266.87249678]; votes 7793; rank 48 |
| Overall ResultCounted from the protocol-matched rows above · 1 tie | 0 benchmark winsNo overall winner | 2 benchmark winsNo overall winner |
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 | Mistral-Medium-3.5-128B | GPT-5.6 Luna |
|---|---|---|
| Developer | Mistral AI | OpenAI |
| Family | Mistral Medium 3 5 128b | Gpt 5 6 |
| Model | Mistral-Medium-3.5-128B | GPT-5.6 Luna |
| Version | Mistral-Medium-3.5-128B | GPT-5.6 Luna |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | Unknown | 2026-02-16 |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 262K | 1,050K |
| Total parameters | 127.7B | Unknown |
| Active parameters | Unknown | Unknown |
| License | other | Unknown |
| Open weights | Yes | No |
| API available | Unknown | Yes |
| Self-hostable | Yes | No |
| Provider access | Unknown | Openai (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, tools |
Mistral Medium 3.5 128B Capabilities
GPT-5.6 Luna Capabilities
Related Comparisons
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|---|---|---|---|
Mistral-Medium-3.5-128BMistral AI | vs | GPT-6 AstraOpenAI | cross-developer peersimage, text |
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Mistral-Medium-3.5-128BMistral AI | vs | Mistral Large 3Mistral AI | family variantsimage, text |
Primary Evidence
Sources and Freshness
Questions
Mistral Medium 3.5 128B vs GPT-5.6 Luna FAQs
Is Mistral Medium 3.5 128B or GPT-5.6 Luna better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Mistral Medium 3.5 128B and GPT-5.6 Luna, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Mistral Medium 3.5 128B or GPT-5.6 Luna?+
Only GPT-5.6 Luna has a directly sourced input price: $0.20 per million tokens. Only GPT-5.6 Luna has a directly sourced output price: $1.20 per million tokens.
Which has a larger context window, Mistral Medium 3.5 128B or GPT-5.6 Luna?+
GPT-5.6 Luna has the larger sourced context window. Mistral Medium 3.5 128B supports 262K and GPT-5.6 Luna supports 1,050K.
Which performs better in benchmarks, Mistral Medium 3.5 128B or GPT-5.6 Luna?+
There is no overall benchmark winner: An overall winner requires at least two decisive benchmarks from at least two original publishers.
Can Mistral Medium 3.5 128B or GPT-5.6 Luna be self-hosted?+
Mistral Medium 3.5 128B is the only model in this pair currently marked as self-hostable. Mistral Medium 3.5 128B is open weight; GPT-5.6 Luna is not marked open weight.
Can Mistral Medium 3.5 128B and GPT-5.6 Luna understand images?+
Mistral Medium 3.5 128B is documented with image input; GPT-5.6 Luna is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Mistral Medium 3.5 128B or GPT-5.6 Luna?+
Neither has a larger sourced maximum output. Mistral Medium 3.5 128B is — and GPT-5.6 Luna is 128K.
Do Mistral Medium 3.5 128B and GPT-5.6 Luna support reasoning and tool use?+
Mistral Medium 3.5 128B: reasoning, tool calling, and image input. GPT-5.6 Luna: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Mistral Medium 3.5 128B or GPT-5.6 Luna?+
Mistral Medium 3.5 128B has 0 sourced provider routes; GPT-5.6 Luna has 2, so GPT-5.6 Luna has broader tracked availability.
Which offers better value, Mistral Medium 3.5 128B or GPT-5.6 Luna?+
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.