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GPT Luna Latest vs Qwen3.8 Omni Flash

GPT Luna Latest

~openai

40#255
vs
Qwen3.8 Omni Flash

Alibaba

40#245
Signal-by-Signal Comparison
SignalGPT Luna LatestDeltaQwen3.8 Omni Flash
Capabilities
100
+17
83
Pricing
100
--
100
Context window size
96
+0
95
Recency
100
--
100
Output Capacity
82
0
82
Overall Result
2 wins
of 5
1 wins
GPT Luna Latest wins 2 of 5 signals

Score History

Score History (3 data points)
GPT Luna LatestQwen3.8 Omni Flash
GPT Luna Latest

40

current score

Leader

Tied

right now

Qwen3.8 Omni Flash

40

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

GPT Luna Latest

~openai

Best Value
Per request$0.000350
Daily$1.17
Monthly$35.00
Annual$420.00

Qwen3.8 Omni Flash

Alibaba

Per request$0.000385
Daily$1.28
Monthly$38.50
Annual$462.00

GPT Luna Latest saves you $3.50/month

That's $42.00/year compared to Qwen3.8 Omni Flash at your current usage level of 100K calls/month.

9% cheaper
Choose GPT Luna Latest for cost optimization

GPT Luna Latest pricing:
Input:$0.10/M tokens
Output:$0.50/M tokens
Qwen3.8 Omni Flash pricing:
Input:$0.15/M tokens
Output:$0.47/M tokens
Tie
GPT Luna Latest

~openai

40

Composite Score

Tie
Qwen3.8 Omni Flash

Alibaba

40

Composite Score

Signal-by-Signal Comparison
MetricGPT Luna LatestQwen3.8 Omni FlashWinner
Overall Score
40
40
--
Rank#255#245
Qwen3.8 Omni Flash
Quality Rank#255#245
Qwen3.8 Omni Flash
Adoption Rank#255#245
Qwen3.8 Omni Flash
Parameters------
Context Window1050K1000K
GPT Luna Latest
Pricing$0.10/$0.50/M$0.15/$0.47/M--
Signal Scores
Capabilities
100
83
GPT Luna Latest
Pricing
100
100
GPT Luna Latest
Context window size
96
95
GPT Luna Latest
Recency
100
100
GPT Luna Latest
Output Capacity
82
82
Qwen3.8 Omni Flash
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

GPT Luna LatestEntry Level

Scores 40/100 (rank #255), placing it in the top 12% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Qwen3.8 Omni FlashEntry Level

Scores 40/100 (rank #245), placing it in the top 16% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose GPT Luna Latest when you need:

  • Step-by-step reasoning and chain-of-thought problem solving

Choose Qwen3.8 Omni Flash when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
GPT Luna LatestBest Value
Input cost$0.10/M tokens
Output cost$0.50/M tokens
Cost per quality point$0.015
Est. monthly (1M tokens/day)$9.00
Qwen3.8 Omni Flash
Input cost$0.15/M tokens
Output cost$0.47/M tokens
Cost per quality point$0.015
Est. monthly (1M tokens/day)$9.30

Both models are priced similarly, so the decision comes down to quality and features rather than cost.

Latency & Speed
GPT Luna LatestFaster
Speed score0/100
Qwen3.8 Omni Flash
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

GPT Luna Latest

Customer support chatbot

Suitable for user-facing chat with competitive response times. Qwen3.8 Omni Flash also offers lower per-token costs for high-volume support

GPT Luna Latest

Long document analysis

Larger context window (1050K tokens) can process longer documents, contracts, and research papers in a single pass

GPT Luna Latest

Batch data extraction

Lower output pricing ($0.47/M) reduces costs when processing thousands of records daily

Qwen3.8 Omni Flash

Creative writing & content

Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content

GPT Luna Latest

Image understanding & OCR

Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly

GPT Luna Latest
Which Should You Choose?
Our recommendation:
GPT Luna Latest

GPT Luna Latest and Qwen3.8 Omni Flash are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

GPT Luna Latest
Recommended

by ~openai

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 3% lower pricing; better value at scale
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by Alibaba

Consider for specialized use cases.

Capability Comparison
CapabilityGPT Luna LatestQwen3.8 Omni Flash
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Searchdiffers
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

GPT Luna Latest

~openai

Best Value
$0.7800
estimated monthly cost

Qwen3.8 Omni Flash

Alibaba

$0.8340
estimated monthly cost

GPT Luna Latest saves you $0.0540/month

That's 6% cheaper than Qwen3.8 Omni Flash at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterGPT Luna LatestQwen3.8 Omni Flash
Context Window1.1M1M
Max Output Tokens128,000131,072
Open SourceNoNo
CreatedSep 11, 2026Sep 21, 2026
Last updated: 41m ago

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