MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
Model Comparison · Head to Head

Claude Opus 5 vs Qwen3.8-Max

Claude Opus 5 wins on Overall, Coding; Qwen3.8-Max wins on Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorAnthropic / Alibaba
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose Claude Opus 5 when coding depth, long-context reliability, lower refusal matter most; choose Qwen3.8-Max when lower cost, lower latency, fine-tuning/ecosystem is the priority.

Choose Claude Opus 5 if you…

  • Dependable and stable
  • Strong reasoning depth
  • Strong long-document handling
  • Best for: Deep reasoning, Long documents, Coding

Choose Qwen3.8-Max if you…

  • Top-tier Chinese
  • Balanced multimodal
  • Alibaba Cloud ecosystem
  • Good value
  • Best for: Chinese tasks, Multimodal, Coding
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.

Claude Opus 5 Higher overall
Anthropic · #2 overall
Overall87
Coding97
Multimodal91
VS
Qwen3.8-Max
Alibaba · #4 overall
Overall82
Coding77
Multimodal92

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionClaude Opus 5Qwen3.8-MaxVerdict
VendorAnthropic (US)Alibaba (CN)Different vendors
Released2026.072026.07Qwen3.8-Max is newer
Overall (rank)87 · #282 · #4Claude Opus 5 +5
Coding97 · #277 · #6Claude Opus 5 +20
Multimodal91 · #592 · #2Qwen3.8-Max +1
Context window1M1MTie
Max output128K128KTie
Effective-context9795Claude Opus 5 more reliable
Input $/1M$5$2.5Qwen3.8-Max cheaper
Output $/1M$25$7.5Qwen3.8-Max cheaper
Cache discount90% off80% offClaude Opus 5 deeper
Speed~45 tok/s~55 tok/sQwen3.8-Max faster
TTFT0.9s0.6sQwen3.8-Max snappier
Function calling9088Claude Opus 5 ahead
Refusal rate~7%~10%Claude Opus 5 less restrictive
English9678Claude Opus 5
Chinese8098Qwen3.8-Max
Modalitiestext, imagetext, imageSame
Open weightsNoNoBoth closed
Fine-tuningNoYes
Free tierNo free tierFree credits for new Alibaba Cloud Bailiang users
SOC2 / no-trainyes / yesno / yes
Private deploymentNoYesQwen3.8-Max

Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

Claude Opus 5 leads the overall aggregate by 5 points (87 vs 82). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while Qwen3.8-Max remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a decisive gap: Claude Opus 5 scores 97 against 77. On multi-file edits, SWE-style tickets and long-horizon agent loops Claude Opus 5 needs fewer correction turns; Qwen3.8-Max is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

Qwen3.8-Max leads multimodal 92 vs 91. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

Qwen3.8-Max is faster in interactive use: ~55 tok/s with 0.6s TTFT versus ~45 tok/s with 0.9s TTFT (about 1.2× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.

Context: window vs usable recall

Nominal windows are 1M for Claude Opus 5 and 1M for Qwen3.8-Max. Effective-context scores point the same way as window size — Claude Opus 5 is ahead on usable recall (97 vs 95), so prefer it for long-document work where details cannot be missed.

Price & total cost

Qwen3.8-Max is the cheaper API at $2.5/$7.5 versus Claude Opus 5 at $5/$25 per 1M input/output tokens — list input is about 2.0× lower. Cache discounts (Claude Opus 5 90% vs Qwen3.8-Max 80%) shift the effective bill, worked out below.

Chinese vs English

English: Claude Opus 5 96 vs Qwen3.8-Max 78. Chinese: 80 vs 98. For Chinese-language production, Qwen3.8-Max is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: Claude Opus 5 90 vs Qwen3.8-Max 88, so Claude Opus 5 has the edge on structured tool use. Fine-tuning is available from Qwen3.8-Max. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Scenario · per monthClaude Opus 5Qwen3.8-MaxGap
List priceno cache applied$1,250100M in × $5  +  30M out × $25$475100M in × $2.5  +  30M out × $7.52.63×gap
With caching90% of inputs cache-hit$84590M cached in × $0.5  +  10M in × $5  +  30M out × $25$29590M cached in × $0.5  +  10M in × $2.5  +  30M out × $7.52.86×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose Claude Opus 5 (coding 97 vs 77).
IF you serve real-time users and latency is a product KPI  →  choose Qwen3.8-Max (~55 tok/s, 0.6s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose Qwen3.8-Max ($$2.5/$$7.5 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose Claude Opus 5 (effective context 97 vs 95).
07

Frequently asked questions

Is Claude Opus 5 worth the higher price over Qwen3.8-Max?
At list the input rate is 2.0x higher, but cache discounts and output pricing narrow the effective gap. Pay the premium when Claude Opus 5's stronger dimensions protect revenue; for routine volume Qwen3.8-Max is the economical pick.
Which is better for agentic coding?
Claude Opus 5 is decisively stronger for coding (97 vs 77 on the aggregate). The gap shows on SWE-style multi-file tasks and long agent loops that need fewer correction turns; Qwen3.8-Max is fine for routine scripts.
How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, Claude Opus 5 is about $845/month and Qwen3.8-Max about $295/month after cache discounts ($1,250 and $475 at list).
Does the bigger context window actually matter?
Nominal windows are Claude Opus 5 (1M) and Qwen3.8-Max (1M), but usable recall follows the effective-context score (97 vs 95). Prefer the higher effective-context model for long-document work where nothing can be missed.
How do they differ for Chinese-language and data-residency use?
Qwen3.8-Max is the Chinese model (Chinese score 98, domestic cloud, possible private deployment) while Claude Opus 5 is the global model (Chinese 80, overseas API). Pick by language quality, access path and where data must reside.
Which one supports fine-tuning?
Qwen3.8-Max supports fine-tuning; Claude Opus 5 does not at this tier. If you plan to adapt the model to a narrow domain, that is a concrete differentiator.